{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:19:57.988170Z",
     "iopub.status.busy": "2024-03-28T14:19:57.987581Z",
     "iopub.status.idle": "2024-03-28T14:20:02.972061Z",
     "shell.execute_reply": "2024-03-28T14:20:02.971401Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pymc version:  5.9.2\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.insert(0, './repos/cogms/')\n",
    "import cogms\n",
    "\n",
    "import pymc as pm\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import arviz as az\n",
    "import numpy as np\n",
    "import torch\n",
    "import time\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set_theme(style=\"ticks\")\n",
    "\n",
    "print(\"pymc version: \", pm.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:20:03.026898Z",
     "iopub.status.busy": "2024-03-28T14:20:03.025979Z",
     "iopub.status.idle": "2024-03-28T14:20:05.013172Z",
     "shell.execute_reply": "2024-03-28T14:20:05.012588Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params_dict = {\n",
    "    \"a\": 2,\n",
    "    \"t\": 0.4,\n",
    "    \"p\": 2,\n",
    "    \"sda\": 0.3,\n",
    "    \"rd\": 0.5,\n",
    "    \"z\": 0.5\n",
    "}\n",
    "params = np.array(list(params_dict.values()))\n",
    "# results = cogms.SSP_trial(params, -1)\n",
    "true_data = cogms.utils.experimenti_simulator(params,cogms.SSP_trial,120)\n",
    "sum(true_data.response == -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:20:05.018177Z",
     "iopub.status.busy": "2024-03-28T14:20:05.017970Z",
     "iopub.status.idle": "2024-03-28T14:20:05.416945Z",
     "shell.execute_reply": "2024-03-28T14:20:05.416183Z"
    }
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "try:\n",
    "    # comment: \n",
    "    mnle = pickle.load(open(\"../mnle-for-ddms/trained_models/ssp_condition.pkl\", 'rb'))\n",
    "except Exception as e:\n",
    "    mnle = pickle.load(open(\"../mnle-for-ddms/trained_models/ssp_condition.pkl\", 'rb'))\n",
    "    # print(e)\n",
    "# end try"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:20:05.422091Z",
     "iopub.status.busy": "2024-03-28T14:20:05.421291Z",
     "iopub.status.idle": "2024-03-28T14:20:05.425277Z",
     "shell.execute_reply": "2024-03-28T14:20:05.424734Z"
    }
   },
   "outputs": [],
   "source": [
    "# unit test\n",
    "# add congruency to theta\n",
    "# theta = np.append(params, 1).astype(np.float32)\n",
    "# # to numpy\n",
    "# data = true_data[[\"rt\",\"response\"]]\n",
    "# data.loc[:,\"response\"] = (data.loc[:,\"response\"] + 1) / 2\n",
    "# data = data.to_numpy().astype(np.float32)\n",
    "# aa = mnle.log_prob_iid(\n",
    "#                 torch.tensor(data).to(torch.device(\"cuda\")),  # supply (rt, choice)\n",
    "#                 torch.tensor(theta).to(torch.device(\"cuda\")),  # supply (theta)\n",
    "#             ).cpu().detach().numpy()\n",
    "# np.sum(aa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:20:05.430472Z",
     "iopub.status.busy": "2024-03-28T14:20:05.429992Z",
     "iopub.status.idle": "2024-03-28T14:20:05.436309Z",
     "shell.execute_reply": "2024-03-28T14:20:05.435480Z"
    },
    "notebookRunGroups": {
     "groupValue": "1"
    }
   },
   "outputs": [],
   "source": [
    "def loglike(theta,data,congruency):\n",
    "\n",
    "    data = data[data[\"congruency\"] == congruency]\n",
    "    if data.shape[0] == 0:\n",
    "        return 0\n",
    "\n",
    "    theta = np.append(theta, max(congruency, 0)).astype(np.float32)\n",
    "\n",
    "    # to numpy\n",
    "    data = data[[\"rt\",\"response\"]]\n",
    "    data.loc[:,\"response\"] = (data.loc[:,\"response\"] + 1) / 2\n",
    "    data = data.to_numpy().astype(np.float32)\n",
    "    loglikes:np.ndarray = mnle.log_prob_iid(\n",
    "                    torch.tensor(data).to(torch.device(\"cuda\")),  # supply (rt, choice)\n",
    "                    torch.tensor(theta).to(torch.device(\"cuda\")),  # supply (theta)\n",
    "                ).cpu().detach().numpy()\n",
    "    return loglikes.squeeze().astype(np.float64)\n",
    "\n",
    "\n",
    "# unit test\n",
    "# loglike(params, true_data, -1).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:20:05.441094Z",
     "iopub.status.busy": "2024-03-28T14:20:05.440685Z",
     "iopub.status.idle": "2024-03-28T14:20:05.450142Z",
     "shell.execute_reply": "2024-03-28T14:20:05.449231Z"
    },
    "notebookRunGroups": {
     "groupValue": "1"
    }
   },
   "outputs": [],
   "source": [
    "import pytensor.tensor as pt\n",
    "\n",
    "# define a pytensor Op for our likelihood function\n",
    "class LogLike(pt.Op):\n",
    "\n",
    "    \"\"\"\n",
    "    Specify what type of object will be passed and returned to the Op when it is\n",
    "    called. In our case we will be passing it a vector of values (the parameters\n",
    "    that define our model) and returning a single \"scalar\" value (the\n",
    "    log-likelihood)\n",
    "    \"\"\"\n",
    "\n",
    "    itypes = [pt.dvector]  # expects a vector of parameter values when called\n",
    "    otypes = [pt.dscalar]  # outputs a single scalar value (the log likelihood)\n",
    "\n",
    "    def __init__(self, loglike, data):\n",
    "        \"\"\"\n",
    "        Initialise the Op with various things that our log-likelihood function\n",
    "        requires. Below are the things that are needed in this particular\n",
    "        example.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        loglike:\n",
    "            The log-likelihood (or whatever) function we've defined\n",
    "        data:\n",
    "            The \"observed\" data that our log-likelihood function takes in\n",
    "        \"\"\"\n",
    "\n",
    "        # add inputs as class attributes\n",
    "        self.likelihood = loglike\n",
    "        self.data = data\n",
    "        self.dev = (\n",
    "            torch.device(\"cuda\")\n",
    "            if torch.cuda.is_available() else torch.device(\"cpu\")\n",
    "        )\n",
    "        # self.dev = torch.device(\"cpu\")\n",
    "\n",
    "\n",
    "    def perform(self, node, inputs, outputs):\n",
    "        # the method that is used when calling the Op\n",
    "        (theta,) = inputs  # this will contain my variables\n",
    "        # print(type(theta)) # numpy.ndarray\n",
    "        \n",
    "        logl = np.append(\n",
    "            loglike(theta, self.data, 1),\n",
    "            loglike(theta, self.data, -1)\n",
    "        )\n",
    "        # print(logl.sum())\n",
    "        outputs[0][0] = np.array(logl.sum())  # output the log-likelihood\n",
    "\n",
    "logl = LogLike(mnle, true_data)\n",
    "# unit test\n",
    "# logl.perform((), (params,), outputs=[[[]],[[]]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:20:05.454685Z",
     "iopub.status.busy": "2024-03-28T14:20:05.454274Z",
     "iopub.status.idle": "2024-03-28T14:20:05.500017Z",
     "shell.execute_reply": "2024-03-28T14:20:05.499475Z"
    },
    "notebookRunGroups": {
     "groupValue": "1"
    }
   },
   "outputs": [],
   "source": [
    "with pm.Model() as SSP_pymc:\n",
    "    # a t p sda rd z\n",
    "    a = pm.TruncatedNormal(\"a\", 2, 2, lower = 0.2, upper = 5)\n",
    "    t = pm.TruncatedNormal(\"t\", 6, 0.5, lower = 0.1, upper = 2)\n",
    "    p = pm.Gamma(\"p\", 15, 10)\n",
    "    sda = pm.TruncatedNormal(\"sda\", 0.5, 0.5, lower = 0.1, upper = 3)\n",
    "    rd = pm.TruncatedNormal(\"rd\", 0.5, 0.5, lower = 0.02, upper = 3)\n",
    "    z = pm.Beta(\"z\", 10, 10)\n",
    "\n",
    "    # convert m and c to a tensor vector\n",
    "    theta = pt.as_tensor_variable([a,t,p,sda,rd,z])\n",
    "\n",
    "    # use a Potential to \"call\" the Op and include it in the logp computation\n",
    "    pm.Potential(\"likelihood\", logl(theta))\n",
    "\n",
    "# test\n",
    "# with SSP_pymc:\n",
    "#     pm.sample(1,chains=1,step=pm.Slice())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:20:05.504120Z",
     "iopub.status.busy": "2024-03-28T14:20:05.503929Z",
     "iopub.status.idle": "2024-03-28T14:41:20.531908Z",
     "shell.execute_reply": "2024-03-28T14:41:20.531339Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sequential sampling (4 chains in 1 job)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEMetropolisZ: [a, t, p, sda, rd, z]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 2_500 tune and 2_500 draw iterations (10_000 + 10_000 draws total) took 1262 seconds.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The effective sample size per chain is smaller than 100 for some parameters.  A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n"
     ]
    }
   ],
   "source": [
    "step_kwargs=dict(proposal_dist=pm.NormalProposal, tune=\"scaling\")\n",
    "sampler = pm.DEMetropolisZ\n",
    "\n",
    "# 不能并行 mnle\n",
    "total_samples = 1e4\n",
    "chains = 4\n",
    "tune = draws = int(total_samples / chains)\n",
    "cores = 1\n",
    "\n",
    "def sample_model(\n",
    "    model, init_params:dict, step_class=pm.DEMetropolis, cores=1, chains=1, step_kwargs={}, sample_kwargs={}\n",
    "):\n",
    "\n",
    "    with model:\n",
    "        step = step_class(**step_kwargs)\n",
    "        t_start = time.time()\n",
    "        idata = pm.sample(\n",
    "            step=step,\n",
    "            chains=chains,\n",
    "            cores=cores,\n",
    "            initvals=init_params,\n",
    "            discard_tuned_samples=False,\n",
    "            progressbar=False,\n",
    "            random_seed=2024,\n",
    "            **sample_kwargs\n",
    "        )\n",
    "        t = time.time() - t_start\n",
    "\n",
    "    return idata, t\n",
    "    \n",
    "idata, t = sample_model(\n",
    "    SSP_pymc,   \n",
    "    init_params=params_dict,           \n",
    "    step_class=sampler,\n",
    "    cores=cores,\n",
    "    chains=chains,\n",
    "    step_kwargs=step_kwargs,\n",
    "    sample_kwargs=dict(tune=tune, draws=draws),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:41:20.536397Z",
     "iopub.status.busy": "2024-03-28T14:41:20.536169Z",
     "iopub.status.idle": "2024-03-28T14:41:20.539965Z",
     "shell.execute_reply": "2024-03-28T14:41:20.539382Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1272.7289235591888\n"
     ]
    }
   ],
   "source": [
    "print(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:41:20.546134Z",
     "iopub.status.busy": "2024-03-28T14:41:20.545747Z",
     "iopub.status.idle": "2024-03-28T14:41:20.625444Z",
     "shell.execute_reply": "2024-03-28T14:41:20.624931Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_3%</th>\n",
       "      <th>hdi_97%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>1.987</td>\n",
       "      <td>0.123</td>\n",
       "      <td>1.777</td>\n",
       "      <td>2.226</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.004</td>\n",
       "      <td>535.0</td>\n",
       "      <td>898.0</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>t</th>\n",
       "      <td>0.454</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.437</td>\n",
       "      <td>0.471</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>527.0</td>\n",
       "      <td>764.0</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p</th>\n",
       "      <td>1.488</td>\n",
       "      <td>0.151</td>\n",
       "      <td>1.223</td>\n",
       "      <td>1.790</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.005</td>\n",
       "      <td>395.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sda</th>\n",
       "      <td>0.697</td>\n",
       "      <td>0.397</td>\n",
       "      <td>0.102</td>\n",
       "      <td>1.405</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.014</td>\n",
       "      <td>349.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rd</th>\n",
       "      <td>0.601</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.021</td>\n",
       "      <td>1.241</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.012</td>\n",
       "      <td>377.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>z</th>\n",
       "      <td>0.664</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0.708</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>433.0</td>\n",
       "      <td>864.0</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  ess_tail  \\\n",
       "a    1.987  0.123   1.777    2.226      0.005    0.004     535.0     898.0   \n",
       "t    0.454  0.009   0.437    0.471      0.000    0.000     527.0     764.0   \n",
       "p    1.488  0.151   1.223    1.790      0.008    0.005     395.0     700.0   \n",
       "sda  0.697  0.397   0.102    1.405      0.020    0.014     349.0     365.0   \n",
       "rd   0.601  0.365   0.021    1.241      0.018    0.012     377.0     366.0   \n",
       "z    0.664  0.023   0.624    0.708      0.001    0.001     433.0     864.0   \n",
       "\n",
       "     r_hat  \n",
       "a     1.01  \n",
       "t     1.01  \n",
       "p     1.02  \n",
       "sda   1.02  \n",
       "rd    1.02  \n",
       "z     1.01  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.summary(idata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:41:20.630232Z",
     "iopub.status.busy": "2024-03-28T14:41:20.630047Z",
     "iopub.status.idle": "2024-03-28T14:41:20.696940Z",
     "shell.execute_reply": "2024-03-28T14:41:20.696430Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a      1.987\n",
       "t      0.454\n",
       "p      1.488\n",
       "sda    0.697\n",
       "rd     0.601\n",
       "z      0.664\n",
       "Name: mean, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.summary(idata)[\"mean\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:41:20.701473Z",
     "iopub.status.busy": "2024-03-28T14:41:20.701292Z",
     "iopub.status.idle": "2024-03-28T14:41:21.290871Z",
     "shell.execute_reply": "2024-03-28T14:41:21.290282Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABssAAAORCAYAAAC0s5x8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3jddfn/8ddZ2XunGU2TtOnei02LqIg4UES/ivOLA8Wv4g8FF/pT0J+KgqB+UUBFnCCIAg5WWWV00JnupNl77+Sc8/n98TnnlNKkSZqcfM45eT6ui+uyOSfJ3Rbpu5/X+75vm2EYhgAAAAAAAAAAAIBZyG51AQAAAAAAAAAAAIBVCMsAAAAAAAAAAAAwaxGWAQAAAAAAAAAAYNYiLAMAAAAAAAAAAMCsRVgGAAAAAAAAAACAWYuwDAAAAAAAAAAAALMWYRkAAAAAAAAAAABmLcIyAAAAAAAAAAAAzFqEZQAAAAAQYgzDsLoEAAAAAJg1CMsAAAAAIIQ89dRT+spXvmJ1GQAAAAAwazitLgAAAAAAcMJvfvMbq0sAAAAAgFmFzjIAAAAAAAAAAADMWjaDYfgAJmBwcFA/+9nP9O9//1v19fWKiorSihUr9OUvf1mLFi2yujwAAICIcNVVV+nVV18N/Pi+++7Thg0bLKwIAAAgcmzevFmXXXaZBgYG9PDDD8tut+uCCy7QV7/6VaWkpFhdHgALEZYBmJDPf/7z2r59u6677joVFhaqqqpKt99+u5KSkvTYY4/JZrNZXSIAAEDYO3r0qK6//npJ0k033aTS0lIlJCRYXBUAAEBk2Lx5s3p6ejR37lx9+tOfVnt7u2699VYVFRXpT3/6E8+3gFmMnWUAxjU8PKy+vj59/etf19ve9jZJ0vr169Xb26vvf//7am1tVWZmpsVVAgAAhL/Xh2MrV660thgAAIAIZLfb9etf/1qJiYmSpLS0NH32s5/V888/r/PPP9/i6gBYhbAMwLiioqJ0zz33SJKamppUWVmp48eP65lnnpFkhmkAAAAAAABAqNu8eXMgKPP/2Ol0atu2bYRlwCxGWAZgQp5//nndcsstqqioUHx8vBYuXKi4uDhJEtNcAQAAAAAAEA6ys7NP+rHdbldqaqq6urosqghAKLBbXQCA0FddXa3PfvazWrRokZ544gnt2LFDf/jDH7Rp0yarSwMAAAAAAAAmrKOj46QfezwedXR0KC0tzaKKAIQCwjIA49q3b5+Ghob0yU9+UoWFhYFlp88//7wkOssAAACmk93OX9MAAACC5bnnnjtppchTTz0lt9uts846y8KqAFiNMYwAxrVkyRI5nU798Ic/1Mc//nENDw/roYce0pYtWyRJ/f391hYIAAAQQZKSkvTaa6/ppZde0uLFi5WcnGx1SQAAABGjoaFBn/nMZ/ThD39YDQ0N+vGPf6zzzjtPGzZssLo0ABbiyiKAcc2dO1e33nqrmpqa9JnPfEbf/OY3JUm/+93vZLPZtH37dosrBAAAiBwf/OAH5XK5dPXVV+u5556zuhwAAICIcumll6qwsFBf+MIXdMcdd+jd73637rzzTqvLAmAxm8H8NAAAAAAAAABAhNu8ebPWr1+v73//+1aXAiDE0FkGAAAAAAAAAACAWYuwDAAAAAAAAAAAALMWYxgBAAAAAAAAAAAwa9FZBgAAAAAAAAAAgFmLsAwAAAAAAAAAAACzFmEZAAAAAAAAAAAAZi3CMgAAAAAAAAAAAMxahGUAAAAAAAAAAACYtQjLAAAAAAAAAAAAMGsRlgEAAAAAAAAAAGDWIiwDAAAAAAAAAADArEVYBgAAAAAAAAAAgFmLsAwAAAAAAAAAAACzFmEZAAAAAAAAAAAAZi3CMgAAAAAAAAAAAMxahGUAAAAAAAAAAACYtQjLAAAAAAAAAAAAMGsRlgEAAAAAAAAAAGDWIiwDAAAAAAAAAADArEVYBgAAAAAAAAAAgFmLsAwAAAAAAAAAAACzFmEZAAAAAAAAAAAAZi3CMgAAAAAAAAAAAMxaTqsLACKJYRh6aW+DDlZ1qGxuqs5eliubzWZ1WQAAAAhxhmHoP69Uye32atPaAsXFuKwuCQAAYEIMw9C28ibtr2hTTnqcNq0pUEw0j50BhBebYRiG1UUAkeKuh/fo0RcqAz++6pJFet+bFlhYEQAAAMLBi7vr9f37tkmSlpVk6JZrzrG4IgAAgPEZhqF7/r5fjzx3LPCxBYUp+s6nzubyD4CwwhhGYJocq+3UYy+aQVnZ3FRJ0v3/OqCaph4rywIAAECI83gN3fvo/sCP9x5r1ZGaDgsrAgAAmJiX9zUGgrJzls9RXIxTh6s7dfcj+yyuDAAmh7AMmCYPPH1EhiGdvzJPP/r8+dqwJEeGIf31mSNWlwYAAIAQVlHXqeb2fsXFOLVxaY4k6d8vV1lcFQAAwOm5PV7d+w8zFHvv5vm64SPr9I2Pb5AkPfFqtQ5Xc/kHQPggLAOmQW//sF7d3yhJunxTqSTpiovmS5Ke3VmnvoERy2oDAABAaNt1uEWSOX7xLRuLJEl7jrRaWBEAAMD4nt1Zq8a2fqUkRgfWkCwtydAFq/IlSU++Wm1leQAwKYRlwDR4cU+9RtxeFeUmqTgvWZJUNjdN+VkJcnu82nagyeIKAQAAEKp2HzHDspULMgPjvBva+tTTP2xlWQAAAGMyDEMPbTkqSXrn+SWKjXYGXtu8rkCS9NLeBnm8hiX1AcBkEZYB02BbuRmGnbcyTzabLfDxs5fPkSRt3VNvSV0AAAAIbR6voQPHzRFFy0szlBgXpTkZ8ZKkI9WdFlYGAAAwtuMN3apu7FGU065Lzio66bXlpRlKiHWps3dIByrbrCkQACaJsAyYohG3V3uOmreBVy/MOuk1/86JXYdbuEkDAACAU9S39Gp4xKPoKIfyshIlSfMLzO6yIzXs+QAAAKHpRd/F8NULsxQf6zrpNafDrjULsyWdGDcNAKGOsAyYokNV7RoY8ig5IUrFc5JPeq04L0VxMU4NDLlVWd9lUYUAAAAIVcfruyVJRTlJctjNCQWlBSmSpArOjwAAIET5pyid45uq9EbL52dIkvYcZQ8rgPBAWAZMkf8P/RWlmbLbbSe95rDbtKgoTZJUXkHbOQAAAE7mD8SK5iQFPpaflSBJqm/ps6QmAACA06lu7FZNU6+cDpvWLc4Z9T0r5mdKkg5Xd6h/cGQmywOAM0JYBkzRfl8ItrQkfdTXlxSbH99HWAYAAIA38E8fKM47MaHAv7OsvrVPXkZ5AwCAELN1b4MkaeWCU0cw+mWnxSkrNVYer6HD1YyWBhD6CMuAKRhxe3WwyvwDf3Hx6GHZ0mKz7by8sk2GwcMOAAAAnFDV2CNJmptzorMsKy1ODrtNwyMetXcPWlUaAADAqF7cffoRjH5lc81pS0dqOoNdEgBMGWEZMAUVdZ0aHvEoMS5KBb6F7G9UWpCiKKddXb3Dqm3uneEKAQAAEKoGh9xq7RyQJBVknzhLOh12ZafFSZLqWzk/AgCA0FHX0qvjDd1y2G3asHT0EYx+8317WOksAxAOCMuAKTjk6ypbWJR6yr4yP5fTroW+vWX7GcUIAAAAn7oWMwhLio9SUnzUSa/NyUzwvYe9ZQAAIHRs3WN2la2Yn6nEuKjTvndBYaokOssAhAfCMmAKDvluxpT5/vAfy+J55ojG8krCMgAAAJj8YVmeLxh7Pf/esoZWwjIAABA6/GHZ2ctzx31vSV6y7DaprWtQHYyWBhDiCMuAKThS3SnpxE2ZsSwoTJEkHavrCnJFZ65/cETP7KhRTVOP1aUAAADMCv4R3flZp4ZlmamxkqQ235hGAAAAqzW29elobZfsNmnj0vHDsphop7LTzQtA1TxvAhDinFYXAISrrt4hNbSZN33njxOWFeclS5Jqm3o0OOxWTFRo/V+vo3tQX7ztWbV1DSo+xqn/d+15Jy2ZBwAAwPSrC4Rlp+6+zUgxw7IWwjIAABAiXtxtdpUtLclQckL0hD6nMDtRDa19qmnq0Yr5mcEsDwCmhM4y4Az55y3nZSYoIdZ12vemJcUoJTFaXkOqauiegeom53f/PKC2LrMdvm/QrV8+vNfiigAAACKf/+JVrm/k4uv5w7LWLsIyAABgPcMw9OS2aknS+avyJvx5hTnmpaDqRjrLAIQ2wjLgDB327Svzj1g8HZvNFuguqwixUYzt3YN6ynfY+T8fXCNJ2nesVZ09Q1aWBQAAEPFaOswgLMs3cvH1Mn1hWVvXoDxeY0brAgAAeKPyynbVNvcqJsqh81ZOPCwryPaFZYxhBBDiCMuAM+QPy8rGGcHoV+ILy0Jtb9nL+xrkNcyfxwWr81WanyyvYX4cAAAAwTE04lFnr3k5KSst7pTXUxJjZLfb5PUa6uwZnOnyAADALOXxGtp5qFnPv1anoRFP4ON/euKQJOm8lXmKizn9hKXXK8w+0VlmGFwAAhC6QmtxEhAmDMPQ4epOSePvK/MrDtGwbOsec9702cvNxaxnLZujo7Vd2nmoWW89q8jCygAAACJXS0e/JCk22jHqSG+H3aa0pBi1dg6opXNA6cmndp8BAABMp4Eht2759avadaRFkjkW+oqL5qu9e1C7DrfI6bDpfW9aMKmvmZeVIJtN6ukfVlfvsFISJ7brDABmGmEZcAYa2/rV0z8sp8OueXOSJ/Q5JXkpksydZW6PV07H9Dd2Do945HDY5bDbJvT+7r5h7T3WJskMySRpSXG6JOlQVbsMw5DNNrGvBQAAgIlr9o1gzEyNG/O8lZkSq9bOAbV2DkhzZ7I6AAAwG939yD7tOtIih92mKJddrZ0D+sVf9wRev3zTfOWkn7pr9XRiopzKSYtXQ1ufapp6CMsAhCzCMuAMHPKNYCzJS5bLObHQKzstTnExTvUPulXT1DPhkG0ivF5Df/j3QT349BHFRDv1mcuX64LV+eN+3qv7G+X1Gpo3JymwWL4kP1kOu03t3UNq7RxU5ig7NAAAADA1/s6yrNRTRzD6Zfj2lrV2MoYRAAAEV11Lr5707bT/v586S2Vz0/T4i5V6aW+DunqHdO7KPH3wLQvP6GsXZCeqoa1P1Y3dWlaaMZ1lA8C0ISwDzsARX1i2YO7ERjBKkt1u07w5ydpf0aaKuq5pDcv+9fJx/fnJw5KkvoER3fan15SXlaDS/JTTft5Le829ZP6uMsm88TNvTpKO1nbpUHW7MlMnvrQVAAAAE9MS6Cwb+2JSapJ585qdZQAAINj+9uwxeb2G1i3O1vLSTEnSuy8s1bsvLJ3y1y7ITtCr5VJ1U8+UvxYABMv0z4EDZgF/Z9mCgpRJfV5JvhmQVUzj3rKe/mH99rFySdJVlyzSmoVZcnu8+uXDe0+7OHXE7dXuo+YM6o1Lc056zb+H7WhN57TVCQAAgBOaJ9BZlpoYI0nq6BmakZoAAMDsNDDk1rM7ayRJ77qgZNq/fmFOkiTCMgChjbAMmKQRtzcQdi0onHhnmWSObZSkY9MYlj2zo0b9g27NzUnUezbP17XvW6noKIcOHG/XK/sbx/y8Q1XtGhr2KCUhWkW5SSe9Njc7UZJU29w7bXUCAADghMDOspTTdJYl+jvLCMsAAEDwvLi7XgNDHs3JiNeykukfk1joe85U3UhYBiB0EZYBk1RR16kRt1dJ8VGBPV8TVZyX4vsaXfJ6x+76mijDMPTEK+Y86UvOKpLDblN6cqzecV6xJOnBp46M2V22+0irJGl5acYpS+Xzs/xhGYcYAACAYJjIzjJ/Z1l7N2MYAQBA8PjXdFy4Ov+UZ0TTIT87QTab1N03PKlLQL39w9qys1Z//M8hPfdardwe77TXBgB+7CwDJulglTmCsWxu6qQPEAVZCYpy2jUw5FZje5/mZCRMqZam9n4db+iW02HTBavzAx+/7Lxi/e3ZYzpU3aHyynYtKU4/5XNfO9wsSVo+P/OU1/Kzzboa2/rl9njldJCrAwAATBePx6vWLjMAy0qbyM4yOssAAEBwDAy5A8+INi7LDcr3iIlyKjstTo1t/apu6lZK4qnPol7vWG2nfv3ofu071ibP6y6bz5tzRN/99DlKio8KSp0AZjeegAOTdOB4uyRp4dy0SX+uw2HXXN/Iw2O1Ux/FuO9YmyRpfkGqEuJOHBRSE2O0eW2BJOmhZ46e8nmdPUM67Nu7tnZR1imvpyXFKDbaIY/XUENr35TrBAAAwAlt3YPyeg05HbZA99hoUnxjGLv6huThJjUAAAiCnYeaNeL2Kic97pQ1HdOpMNu3t2ycUYxVDd362i9e1O4jrfJ4DRXmJGrTmnwlxLpUWd+t/3fftqDVCGB2IywDJumQLyxbVDT5sEySin17yyrrpyEsqzBHKS4tObVz7N0Xlspmk14tb1R1Y/dJr20/0CjDkErzk5WefOptZpvNprxMs7uMvWUAAADTq8W3rywjJVZ2+9iTCpLio2W322QYUlff8EyVBwAAZpGXfSMYNy7NDcoIRr/CnPH3lnm9hu74yy71Dbq1qChNv7zxTfrZ9Zt13X+t0Q+uPU9Oh117jrbqoO/ZHABMJ8IyYBJaOwfU2jUou92m+QUpZ/Q1/GHZsbqph2X7K8zOstHGLOZlJmjjUrN9/uEtx0567fnd9ZKk9UvGbq+f4wvLGloJywAAAKZT8wT2lUmSw25TSoI5PaCDvWUAAGCajbi92lbeKEmBZ0jBEgjLmsYOy17a26BD1R2KjXbqKx9eq9yM+MBrBdmJutC3guQfz1cEtVYAsxNhGTAJB6vMmytFuUmKiT6zlX+BzrIphmWtnQNqbOuX3TZ2l9t7NpVKkrbsrFFbl3mDuaVjQK8dMmdRX/i6PWdvlJ1mPrxpau+fUp0AAAA4mT8sy0wde1+ZX4pvTGMHe8sAAMA023esVX2DbqUkRGvhGU5QmqjCbH9nWbcMwxj1PU9vr5Ekvf3ceaNOQnrrWXMlSdsPNjGiGsC0IywDJuHEvrLUM/4aRTlJstnMBx5TuSHs7yorzktWXIxr1PeUzU3TkuJ0uT2G/v6ceevm8a2VMgxpWUnGSTd03ig7zXyNsAwAAGB6+ccwjtdZJkmpvr1ldJYBAIDp9tI+cwTjhqU5cpxmNPR0yM9OlN0m9fSPqHOUS0DdfcPacbBJ0tiXu0sLUpUQ61L/oFtHajuDWS6AWYiwDJiE8kpfWDaF2zYx0c7APrCKKewtOzGCMeO07/N3lz22tVL/fvm4/v6cOZLxHecXn/bzstPMGzz+m88AAACYHs3t/jGM43eWpdJZBgAAgsDrNfTKvhP7yoIt2uVQdrp5MXu0vWUv7qmXx2uoeE6yCnOSRv0aDrtNy+ebz8F2H24JXrEAZiXCMmCCunqHdMx3a2V56ekDqvEUzzFHMVZMYRTjvopWSaPvK3u9NQuztWpBpoaGPbrzgd0adnu1pDhdG5bknPbzTnSWDYzZHg8AAIDJa/Z1lmVOpLMsyddZ1kNnGQAAmD6HazrU3j2k2GinVsyf2nOuifKPYqxq6j7ltWd31kqSLjjNyhBJWjE/U5K0z3eJHACmC2EZMEF7jrTKMMx9ZaPNTZ4M/96yMw3LOnuGVNPUK0laPO/0XW52u01f/vA6bViSI5fTrpULMnX9h9bIZjt9e31GSqzsNml4xDNqezwAAAAmzzAMtXROfAxjin8MI+cxAAAwjV7ea3aVrV2ULZfTMSPfszDHv7fs5M6y5o5+7a9ok80mnb8q77RfozQ/RZL5TI3L3QCmk9PqAoBwseOQOTd5VVnWlL/WvCmGZeWV5u2ZuTmJSk6IHvf9CbEuff3jG2QYxrghmZ/LaVdacqxaOwfU1NGv1KSYM6oVAAAAJ3T1Dmt4xCObzbycNB7/GEYuLwEAgOliGIZe8oVlZ83ACEY//+Xxo2/YN/bca3WSpKXFGeOej4pyk2S329TdN6y2rsEJnacAYCLoLAMmwOM1tK3cDMvWLpp6WOYfw1jf2qf+wZFJf/6JfWWnH8H4RhMNyvyy08zbzk1t7C0DAACYDv59sKmJMXI5x//rWJrvwlJHN2MYAQDA9Khp6lF9a5+cDrvWTMNzrokqKzSnI1XWd2twyB34+IkRjKfvKpOkKJcjMM7x2BtCNwCYCsIyYAIOHm9Xd9+wEmJdWjJvcgHVaFISo5WRbD74OHYG3WX+ucxLi4M7U9oflvkf6gAAAGBqWjr8Ixgndgs6lTGMAABgmr20z+wqW7kgU3Exrhn7vhkpMUpLipHXawS6y443dOt4Q7ecDpvOWT5nQl9nqutNAGA0hGXABLy4p16StH5JjhyO6fm/zfzCVEnSkeqOSX1e38CIKuvNw8Di4tPvK5uqQGdZO2EZAADAdPBfQprIvjLpxM6ygSH3STewAQAAztTL+xolSRuX5szo97XZbFpYZD4PO3C8XdKJrrI1C7OVEBc1oa8zb06SJKmqqWecdwLAxBGWAeNwe7x67jXzD+5zV0zshstElPnCskOTDMvKK9tkGFJuRrzSk4M7l5kxjAAAANPLH5ZlTrCzLDbaqegohyS6ywAAwNR19Q4FxheuWzyzYZkkLSsxpyS9tLdBbo9XW3xh2YVr8if8NfKzzDGMdc29018ggFmLsAwYx86DzerqHVZKQrRWl03fHOcFvrDscHXnpD5vf2AE49THQY4nyx+WMYYRAABgWvjHMGZOsLPMZrMFRjG2s7cMAABM0Z4jrTIMqSg3KbAbdSaduyJPdrtNR2o6dd/jB9TaOaCUxOhJBXf5WQmSpLqWXnm8RrBKBTDLEJYB43h6e40k6YLV+dM2glGSSgtSZLdJrZ0Dk3rw4d9XtmQGwjJ/Z1lLRz+HDwAAgFF4vIa+c88ret9XH9P379smwzj9menEGMaJTwhITTQfZHX20lkGAACm5rXDzZLMfWVWSEmM1pqF5mX0h7cclSS9Z1Opol2OCX+NzNQ4uZx2jbi9auGCN4BpQlgGnEZP/7Be2W/Ocb5oXcG0fu3YaKcKc8wZy4cnOIpxcMitozWdkqSlvrb1YEpPjpXDbpPbY6i9i5vMAAAAb7R1d71eLW/UwJBbL+6u17byptO+399ZNtGdZdKJvWWddJYBAIApMAxDrx1ukSStWjB905Mm6+OXLQmcb5aXZuhtZ8+b1Oc77DblZZrdZbWMYgQwTQjLgNN4YVed3B6vinKTNG9O8rR//fkFKZImHpYdquqQx2soIyV2UreRz5TDbgvs02jmpg4AAMApHnzmyEk//suTh8d8b//giHoHRiRNfGeZpMCIpFDeWdbSMaDHt1aquZ0zIwAAoaqupVetnQNyOuxaXJxmWR35WYm67YsX6IYPr9O3P3mWoibRVeaXl+UPy3qmuzwAsxRhGXAa/hGM091V5lc217+3bGJh2d5jrZLMfWU2my0oNb2R/9Yzbe0AAAAna27vV0Vdl+x2m352/SZJ0qHqDnWM0QHm7ypLiHUpLsY14e8T6jvL+gdH9PX/fVG/+OseXfPDp1VZ32V1SQAAYBSvHTK7yhbPS1NMlNPSWtKTY3XOijlynuHKk/wsOssATC/CMmAMdS29OljVIbvdpgtW5QfleywoPBGWuT3ecd/vnyu9vDQ4Ixj379+vq6++Whs3btSGDRv08Y9/XEa/OYay2fdwBwAAACb/2aysMFWFOUkq9U0N2HFw9FGMTYF9ZRMfwShJKYlT7yxrbW3Vl770JW3YsEFr1qzRddddp+bm5kl9jd/+9rcqKytTbW3tSR+/5rqbtOU3n9XhR7+svQ99SW/dtF5lZWW65557zrheAAAw/fyXsK3aVzZVn//853XDDTdIMrvTJKmmafTOsg984AMqKys75Z+9e/fOWL0Awou1VwiAEPaMr6tsdVmWUn2jb6bb3JwkJSdEqat3WIeqOrSkOH3M9/b0D+uIb1/ZqrLpnytdVVWlD33oQ1q6dKluvvlm2Ww23XvvvXrk199S/jmfV0tn0bR/TwAAgHDmv53tP5utXZitozWd2n6gWW9aP/eU9ze29kmScjImF5alJvl2lvWcWWeZ2+3W1Vdfrd7eXn3rW9+S2+3Wrbfeqk984hN66KGH5HKN3+VWWVmpH//4x6d8fMTtUXn5AcWmF+v9V31KT26rltNh1zc/sUGlxaf+GgAAAGsYhqEDx9sl6bTPn0KR1+vV9773Pf373//Wu9/9bkmn7ywzDEOHDh3Sxz72Mb31rW896bWSkpLgFwwgLBGWAaPweg09vcMMyzavCc4IRkmy221aMT9Tz71Wp9cONZ/2sLLrcIsMQyrITlRGyvTvK/vd736n2NhY3XXXXYqLMx/gbNy4Ueedf6E6KrequWPptH9PAACAcGUYhvZXtkmSVsw3u/5XLsjUn544pPLKNhmGccrY7IY2MyzLTY+f1Pfyj2E8086yf/3rXyovL9djjz2m0tJSSdKiRYv09re/Xf/85z/1jne845TPGXF75PEYiol2yuPx6MYbb1RKSooaGxtPet/LexvV11GnnNKNuv5T71R1z9OqaeqVLT5fWVnTf8ELAACcmab2fnX2DMnpsKk0P8Xqcibs4MGD+u53v6u9e/cqJubEZfa8TDMs6+4bVlfvkJITogOvVVdXq6+vTxdccIFWrlw50yUDCFOMYQRGsb+iTS0dA4qPcWr90pzTvnfz5s268847dcstt2jDhg1atWqVvvSlL6mvr0+//OUvdf7552vNmjW69tpr1dFxYjfZAw88oEsvvVS/+d5HVfHkLfrz/ffI4/Gc9LUfeOABXX755Vq5cqU+9cG3qOq5nyh+6Gjg9YceekiLFy/W7t27deWVV2rZsmXatGnTSSNvHnrooVHbzv3/3HHHHZKk4uJiffzjHw8EZZIUFxenjMwsjfS3BXZsAAAAzBanO+fdfscvtPPhb+rov76pO390kzo6OlRakCKnw6bj+5/TWy95m5YuXaoLL7xQd9xxhzwejxp8nWW5GfEnnfOWL1+ud77znfrnP/8Z+N6vP+d95Quf1JHHv6ptD31Td99990nvmcg574UXXtC8efMCQZkklZaWqqSkRM8+++xJP2ePx6s//ueQPvCNf+qKrz6ma37wtL7z/36q1tZWffKTnzzl1+gfW/bJPdiljetWyGG3afE88/LXQd/NdQAAMPNGO8Ncf/318rqH5G16SW+6aNNpn1W98QzzepM5w0z1WZUkfeUrX5HH49Gf//xnpaefuGQeG+0MXCavazm5u+zAgQOSpIULF07DryaA2YLOMmAUT22vliSduzJP0S7HuO+/9957dc455+gnP/mJ9u3bp1tvvVX79+9XVlaWvvOd76i2tlY333yzMjIydNNNN+muu+7ST37yE33oQx/SZz9/nW7++aM6svOfuuFGp374g+9Lkn7/+9/ru9/9rq699lqtXr1at9z9nKr2/keP/fE2fenqdygnxwzxvF6vvvCFL+ijH/2ovvCFL+jBBx/UD37wAy1YsEDnnXeeLrzwQv35z38es3b/1/mv//qvU16rqqpSTVWFkuaeo5aO/lFvSAMAAESysc55MfEpyl7+HiW6+rXlmQf0059m6qabbpK3caua9vxNm97yLn3j61/TgQMHdMcdd6ihoUHtSZslSbte+pd+88vbde2112rNmjXq6urSr371K/2f//N/tGrVqlPOeR/+yEfUlbBRXdWv6oc//KHKysomdc47duyYioqKTnm9sLBQlZWVgR8Pj3j0nXte0a4jLYGPHT16RE8/f7duve1nGuo7OQBrau/X9tfMvR99zQe1adMmNTY1yRWfrWdtV+hjly05s190AAAwZaOdYVzxe5STkz3us6obb7zxpDPMLbfcIunkZ1UTOcNM9VmVJP3gBz9QWVnZqO/Lz0pQa+eAapt7Axd2JDMsi4uL0w9+8AM9/fTT6u/v18aNG3XjjTequLh4On55AUQgwjLgDQaH3Nq6p16StHntxEYwJiQk6Cc/+YmcTqfOPvtsPfzww2pqatIDDzygxERz4ejzzz+vnTt3qqenRz//+c915ZVX6utf/7ok6dHdNu2LitPfH3lQn7z6E5o/f75qamr0iU98Qtdcc42qG7tlJDdpzspEVWy5TTt27NCll14qyRwBdM011+iKK66QJK1Zs0ZPPPGEtmzZovPOO09paWlKS0ub/K/D4KC+8pWvKDo6WilF52hw2KPegRElxkVN+msBAACEq7HOedd8/bt65MU6XbS+ULlRTYFz3tGdjyl57gYtP/8DOvfcFTr33HOVkpKir3/96yreVCRnfLb6uloC5zy/vLw8XX755WOe856s+KdiUos01Hpg0ue8np4eFRQUqqKuS30DI+odGFF6cozi4uLV12d2uw2PePSD323XriMtio126Jr3rNCS4lRdetm7lVy4Xs8edmjDHOOkr/vkq9Ua6jbPzb3dHfrud7+r+uYu3XLrL/TSP36qLW9fqgsvPH+6fisAAMAkvPEMc9e9f1B/T7u+eMOvdMH5iySd/lnV688wH/vYx055VuU33hlGmtqzqrGCMskcxbjrcIvq39BZdvDgQfX39yspKUk/+9nPVFdXp5/97Gf64Ac/qL/97W/Kzs6e+C8kgFmDsAx4g5f2NWhgyKOc9DgtKprYH9zLly+X03ni/04ZGRmKi4sLBGWSlJKSosOHD+u1117T4OCgNm/eLLfbLUlaUZqmyurFkqQXX3xR8+fP1w033CBJ6u7u1l/+8Yy6a3cq1l0nSRoeHj7p+69atSrwv6OiopSWlqb+/n5J5gHljS3zr2e322W3nzyRtbe3V5/97Ge1d+9e3X777frtC2519gypub2fsAwAAMwqY53zatpGJEkl+Smqf905zz0yrITsxdpf0RI4623ebHaU9TQdVub8XN30za/LYbepu7tbFRUVqqqq0iuvvCJp7HNeamK0uvuGlZiUPKlzXnPHgDq6B7V1b72O/HjLSa83766Tt29I9/5jv7aVN6q2uVdOh13f+PhGLSvN0J133qn4KK/SVrxdB463K2HoRGeZx2voyVerlDhnud7/9rN0zccul8PhkGEYeuBVtw7854f6yW23EZYBAGCR159hDMOQ4YiTK96hJfPzAu853bMq6cQZZrRnVRM9w0jT86xqNP69ZfW+Udd+X/ziF/Xf//3fWrdunSRp7dq1Wr16tS655BLdd999uv7668f92gBmH8Iy4A2e3l4jSdq8pmDCIwcTEhJO+djrd3+9XmdnpySNuvNBkuobzKXp1dXV+uY3v6mXXnpJNrtTrvhMrVy+RJUyDxWv9/oFp5J5qPC/5+GHH9aNN944Zu2f+9zndO211wZ+3NDQoE996lOqrKzUT37yE73pTW/S4/ueNcOyjgGVhNESWAAAgKka7ZwXGxurY7WdkqT5BSl63vdx/zmv7tV7VffqvVpyz8mf5x7sVm5GvOpqawLnPJfLpeLi4sBOjbHOeamJMapq7JEh24TPee9470dU4V6mAbdDzqFBJca5lJIYrdhop+pa+jQyPCCP16mHt5g7cRPjXLrhI+u0rDRD5eXl+t///V/96le/Uv1Amn79j/164bVaSeZopVf21qm1a1Bp6Vn61EfeIofDHF1us9mUl52sqswFOnr0lYn9IgMAgGn3+jNMU3u/vF5DDmeU8rNOPduM96yqublZ0snPqiZ6hvGbyrOqsfjDstrmkzvLRttVVlBQoJKSEh08eHDcrwtgdiIsA16nrWtAu307GjZNcATjZCUlJUmSfvSjHwV2RxiGoe/9dptaOwc0d+l6eb1effKTn5TL5dKP7rxXdz3epKgol7581Xy998UnJ/X9Nm3apAcffHDM17OysgL/+9ChQ/rEJz6hoaEh3XvvvYEbOFmpcTpS06mWzv5J/mwBAAAiz4jbq/7eYTnsNhXlJgU+7j/nlZ37EQ0oSZ9893ItnJsqybyQ9c9tLZqbkxA45z344INatGiRnE6njh49qkceeWTM75mSFC1J8npPPIg63TnveH237nq0QrYor7Jz8+Xta9T9375Edrt5GczjNfSWt9yurOIynbVhrornJGnT2gLFxbgkSU899ZRGRkb00Y9+9JSvffHFFyt9zgKlr/5vFSe16pmnn9Rb3vKWwOt5GQkyPCOKT0ieyC8nAAAIssr6LklSTJRTTsepHVujPat6vYyMjJOeVU3mDDOayTyrOp05mfGSpIbWPnm8hhx2m9xut/7xj3+oqKjopO42yVw5ciarSgDMDoRlwOs8s6NWhiEtKU5XTnp8UL7HihUr5HK51NTUpMsuuyzw8fNXNeqXv/ipHvyXTReumavKykp99atf1fbjdtnsDp23Mk/bXt0qybzNO1GpqalKTU0d930NDQ362Mc+JofDoT/+8Y8qLS0NvJaZGitJaukYmPD3BQAAiFQDQ+Z4ork5SYpyOQIf95/zUmKGZcQUaMSVpWXLFurAgQN65C/3yJZ9rjISjMA5b9myZYHPfe655ySNfc5LSzRvZ3tfd2t7rHPe8IhHP3vsGdmiknT28lyVnfMuffWrN6qi4ljgjFdZcUw11cf1P5//nC67bOUpX+N973ufLrzwwsCPjzd065af/kHtR57Usos+rR5PgqKcdg007dONN96mDRs2KCUlRZKUmexUX/NBFZctn8CvJgAACLaKum5JUky0Y9TXx3pWdeDAAf3gBz/QNddco6ioqDM6w4xmos+qxpOZGienwy63x6uWjn7lpMfL6XTqzjvvVFZWlv74xz8G3rt//35VV1fr6quvnvL3BRCZCMsAH8MwToxgDFJXmWQeCP77v/9bt99+u3p7e7VhwwY1NTXpz3ffJs/AkIYc6frHy03Ky8vT3ff+Vo68zXJGxanz8D7d84D5h/zAwPSHVt/97nfV1tamb3/72+rt7dWuXbsCr3kHOiQRlgEAAEhmWBYjqbQg5aSP+895v/rV3Uqa16wt0S2KGzio22+/Xe3dg8qbn6slCwqVl5en3//+98rJyVFSUpKef/553XfffebXHuOclzpKZ9lYntxWrbqWPqUlReva961SlGOlfvnLu3T11VfrS1/6kiTp1ltv1YIFC3TJJZcEPq+8vFxRUVEqLS1Vdna2srOzA68tWyZtefE1PXrkSfUaKYpKSNPHL1uihbmL9fRTT+jqq6/Wpz71KXm9Xv3xFz+T1zOswhVvm8wvKwAACJKKuhOdZaMZ61nV7bffLpvNpoULFyoxMfGMzjDB5LDblJsRryOHD+rVHfv0jjdvkCRde+21+spXvqIvf/nLeuc736n6+nrdfvvtWrRokd797nfPeJ0AwgNhGeBztLZTNU09inLadc7yOUH9Xl/4wheUmZmpP/zhD7r77ruVnJyss846S296x4f1s0cq9diLlSo+++Pa8fTvNbDrz4qJidbRkTL94he/0C233KLt27frqquumrZ6hoeHtWXLFknSTTfddMrrZYtXSMUfVHMHYxgBAADGCssk85xnj0rUr+75rZ47tkX7nk3VWRvP0qGh5bK5YlWUm6Sf//znuvnmm3XDDTcEwqnxznkp/s6yccIywzD0+IuVkqT3bJqvhFhzrOKvf/1r3XzzzfrGN74hl8ulc845RzfeeKOczhN/Jfzc5z6nvLw8/e53vxv1a5+9PFeP/kk6a9kcnbd+ceCC2f33368f//jH+trXvqbh4WEtWbZS3ry3qWMwdtxfSwAAEHwVvjGMsdFjPwoe61nVddddp8TEREk6ozNMsOVlxuvZP9ynXzQ9rXe82Rzt+K53vUtRUVG6++679dnPflaxsbG6+OKLdd111wX2rALAG9mMN25fBGapux7eo0dfqNT5q/J0/YfWWlbHA08d1n2PHwj8+PyVebrug2vk8O2XsMKx2k594SfPKiUhWr/79lstqwMAAMBqhmHog9/8p3r6R/STL1wwamDm8Rr6r288rv5Bt26/7kK5PV596fbnFB/j1B++87bA3rDJ2H2kRV//360qyE7Qz7980ZjvO1TVrv/z0+cV5XLotze9JRCWzaT+wRFd+bXHJUl/ueXS0z6YAwAAwdXdN6wPfvOfkqQ/3/y2wH7SSPGbR/frr88c1dvPmadPXc4IaABnjr+1IKJVN3aruWNAi+elnfYwMOL26tmddZKCO4JxIq64aIGWl2Zof0WbinKTtaosUzabdUGZJGWlxUmSOnuHNDTiUbSLWzgAAGB2au4YUE//iJwOm+bmJo76HofdprLCVL12uEW7DrfI49vhsaw044yCMklKTTTHMHZ0D532fS/tbZAkbVySY0lQJklxMS7FxTjVP+hWa+eACrJH/3UCAADBV+nrKstNj4+4oEyS5mQmSJLqWnotrgRAuCMsQ0QacXv007/s0pYdtZKkzNRYffEDq7WsJGPU9+842KSe/mGlJUVr5fzMmSx1VGVz01Q2N83qMgISYl2KiXJocNij1s4B5fkOIgAAALPN0ZpOSVJRbpJczrEvEG1clqvXDrfomR01Sk6IkqQpnTPTkswxjL0DI2NeXjIMQ1t9YdlZy3PP+HtNh/TkWPUP9hCWAQBgMX9YNi8vyeJKgsP/jKqutc/iSgCEO7vVBQDB8JvHyrVlR61sNsnpsKmlY0Bf+8WL2rKjZtT3/+ul45KkC1YXyOHg/xZvZLPZlJlqdpe1sLcMAADMYkdqOiRJJfkpp33feSvz5HTYdbyhW7uPtEqSViw487As3nd5SZLaOgdGfU9tc68aWvvkctq1uizrjL/XdMhMMfeVtXWNXisAAJgZFXVmWFY8J9niSoLDH5a1dPRreMRjcTUAwhmpACJOZX2X/v5chSTpqx9dr9//30u0eW2BDEP66V926WBV+0nvr2ro1o6DzbLbpEvOKrKg4vCQmWo+8Gju4IEHAACYvcorzbPkwnGmACTGReniDYWBH5+7Yo7ys868w8pmsynDF0C1jBGW7T7SIknjjiCfCSdqHbS0DgAAZjt/WDYvLzLDsuSEKMXHOGUYjGIEMDWEZYg4jzx3TJJ0zvI52rg0V3ExLv3Plau0cWmORtxe3fzrV9Xs644yDEP3PrpfknTWsjnKzYi3rO5QlxXoLJt8WDY45NazO2u1/UDTdJcFAAAwY0bcHh2t7ZRkBlLj+dS7l+tDb12ozWsLdO37Vk75+/u7tcY6j/nDshUhMFY8I9kcG9k6RrAHAACCb3jEo5pmM0AqidCwzGazqcjXNVdZ321xNQDCGWEZIkpH96Ce3VknSXrXhSWBj9vtNl33X2s0b06SOnuG9J17XlFHz6Aee7FSOw82y+mw60OXLLSq7LDgfzjTPMkxjF6voa/ftVU/+v0Offvul7W/oi0Y5QEAAATd0Zoujbi9Sk6ImtAlK4fdpisvLtMXP7B6Wjq9TtdZ5vEa2nvUN+4xFMIyX62tjGEEAMAy1Y098noNJcVHBfafRqJ5c8x9bP79bABwJgjLEFEe21opt8erhXNTTxmNExvt1Nc/vkEpidE63tCtD3/r37rr4b2SpA+9deGUxuLMBlmpp7/JPJate+t1qKoj8ON7/r5PhmFMa20AAAAzYc9R/5jDdNlsthn//v4dsqN1a1U3dqtv0K3YaMe4+9RmQiAso7MMAADLVNSf2FdmxdllphQHOssIywCcOcIyRAyP19C/X6qSJL3zgpJR35OVGqfvf/bcwPJPu016x/nFunxT6YzVGa78D2cm21n2yLPmWMy3nV0kp8OmIzWdamjrm/b6AAAAgu3lfQ2SpLWLsi35/pkp5o3wllHOYwePm7vUygrT5LBb/zDMH5a1EZYBAGCZygjfV+bn//lV1HVzQRvAGXNaXQAwXQ5Xdaizd0jxMU5tXJo75vvyMhP08y9vVmNbnxLiopQUHzWDVYavnHTfzrLOAbk9Xjkd42ftHT2DOlRtdpW9700LVN3Uo33H2rTrcIvmZCQEtV4AAIDp1NIxoKO1XbLZpHWLrQrLTpzH3uigr5N/YdH4u9Rmgj8s6xt0q39wZFrGUAIAgMk5VufvLEuyuJLgKsxOlNNhU0//sJra+5WTPv64bAB4IzrLEDFeLW+UJK1ZmD1ukGO32zQnM4GgbBJSE2MU5bTL6zUmPIpxx4EmGYZUmp+s9ORYrVxg7s947VBzMEsFAACYdv98qVKStKgoTamJ1uz8yErzdfq398vrPfnW9AFfZ9nCotQZr2s0sdFOxceaARmjGAEAmHler6HjDbOjsyzKdWIMdXllu7XFAAhbhGWIGP6wbN2SHIsriUx2u005vkX2Ex2juP2AGYqtW2z+nqz0LZvfX9FGWzwAAAgbjW19evSFCknS5RdaN747KzVWTodNw27vSQFUZ8+QGlrN81nZ3NDoLJOkjGQzVGztGrS4EgAAZp+Gtj4NDHkU5bQrPzPyp/ssnpcuSSqvbLO4EgDhirAMEaGxrU/VjT2y221auzDL6nIiVq6vjd3/MOZ0DMPQvopWSdIKX0g2b06y7HabevpH1N7NQxMAABDaPF5DL+2t1w0/e0EDQx6VFaZqvYUXsxwOu3J9l5dqW3oDHz9UZd6gLsxJVEJs6Iw79I9ipLMMAICZ5z8flOSnyDGBVRrhbpFvFDWdZQDOVOT/lxKzgr+rbMm8dCXEMVoxWPwznxsn0FlW09Sjrt5hRTntWlCYIslsi8/LNL/G8YbuoNUJAAAwVV29Q/rKHc/rlt9sU1vXoPIyE/TVj62XzWaztK48383w+teFZf4RjItCZF+Znz8sayMsAwBgxh08bu4zLZsbGiOag23xPPMcVNPUo57+YYurARCOCMsQEXb4xv2tX2LNsvXZwn+TeSKdZfsqzLb3hUVpcjkdgY8X5Zpzso/XE5YBAIDQZBiGvvfbbTpU3aHYaKfeu3m+fvLFC5SWZM2ustfzh2V1zaeGZQtD7GGYPyxrISwDAGDGHaoyw7KFIXaZJliSE6ID5yT/2QgAJoOwDGHP4/HqwHEzmPGP+0Nw+MOyutfdZB7LvmPm78nS4vSTPl6UmySJzjIAABC6Xt7XoP0VbYpyOXTr/5yvj1y6WLHRTqvLknQiLPOPYewfHNHhavNh2JLiDMvqGk1GMmMYAQCwQt/AiI43dEkKvcs0weTvLiuvYG8ZgMkjLEPYq6zv1sCQR/ExThXmJFldTkQrzE6UZHaWjbi9Y77PMAztO2buK1tacvJDG39YVt3YE6QqAQAApuaR5yokSe88v1gFvvNPqJjrO0sdremU12toX0Wb3B5DOelxgYtNoSI92ezEY1ctAAAza/eRFnkN85JNuu/yymwQCMvYWwbgDBCWIeztrzRviyyaly6H3dodEpEuPTlGsdFOebyGGlrH7i6rb+1TR8+QnA67FrzhBlNOepwkqbG9T4ZhBLVeAACAyeroHlS573z51rOKrC1mFCV5yYqJcqh3YERVjd167ZA5jnzVgiyLKzuVf2wlYRkAADNrp+98sGZh6J0PgmnxPHO60ZGaTg2PeCyuBkC4ISxD2Nvva6323x5B8NhstkB3WU3T2GGZv6usbG6qol2Ok17LSjPDsv5Bt3oHRoJUKQAAwJl5eV+DDEOaX5CirNQ4q8s5hcNh1yLf7pHdR1r1wu56SaH5MCzVF5b19I9oxM0DKwAAZoLXa2j7gSZJ0uoQPB8EU25GvFISo+X2eANjqgFgogjLENYMwwjc/F3yht1YCA7/KKLqprHHKO49Ovq+MkmKiXIqNTFaktTY1heECgEAAM7c7qPmpZ8NS3MsrmRs/jHX9/x9nzp7hpSSEK01i7ItrupUiXEuOR3mXzk7uocsrgYAgNlh77FWtXUNKj7GqWUlobXPNNhsNpuW+LrLGMUIYLIIyxDW6lp61dU7LJfTrvkFKVaXMyv4w7Kqxu5RXzcMQ3t9nWXLSkc/lOWkm/s0mtr7g1AhAADAmTta0ylJWlgYulMLLlydryjnib/KbVpbEAilQonNZlNaknlJqr2HUYwAAMyEJ1+tliSduzJPUW+Y9jMbLC42z3D+tS0AMFGh9zcqYBL2V5i3RBYUpsrlnH0HACuU5CVLOvEg6Y0aWvvU3j0op8OuhUWjP2TK9o1ibGwjLAMAAKGju284cJmnJIQvYmWlxeljly2RJK0uy9KVb1pgcUVj849i7GBvGQAAU+b1Gqpp6lFX7+gd27sPt+jZ12olSRevL5zJ0kKGv7Ps4PF2ebyGxdUACCdOqwsApoIRjDOv1PfgqKm9X129Q0pOiD7p9b2n2Vfml53uD8sYwwgAAELH0dpOSdKcjHglxLqsLWYcbz+3WOevyldinEs2m83qcsaU5gvL2rsIywAAmIre/mF961cv65BvF9eCwhStX5yjotwktXYN6mBVu55/rU6GYQZlZXNDt0s+mIrmJCs22qn+QbeO13epJD/F6pIAhAnCMoS1/RW+sGweYdlMiY91KT8rQbXNvTpS06m1b9iP4d9Xdrq52NmpZljW0jEQvEIBAAAm6ZgvLCsN4a6y10uKj7K6hHH5d9W297CzDACAqfjVI/sCQZkkHa7u1OHqzlPed/byXF39rmUzWFlocdhtWlSUpp2HmlVe2U5YBmDCCMsQttq6BtTU3i+7TVpYlGp1ObPKgsJU1Tb36lBVx0lhmbmvrEWStHyMfWWSlJ4SK8n8PQQAAAgVdS29kqRC345WTF0aYxgBAJiy3v5hPb+rTpL0/c+eq9yMeG0rb9KOg01q7RxQSmK0CrMTtXFZrsoKU0O663wmLC42w7L9lW267Lxiq8sBECYIyxC2/F1l8/KSFRcT2mNyIs3CojQ9vb1G+ypaT/p4XUuv2ruH5HLaVTZ37AAz3ffQpI1xPAAAIITUt5gjoudkJlhcSeQIjGEkLAMA4Iw9t6tOI26vinKTtHhemmw2m96yca7esnGu1aWFJP8EqvKKNhmGMevDQwATY7e6AOBMMYLROivmm11jB4+3a3DIHfj4q/ubJEmL56Upaox9ZZKUnmw+NOkdGNHQiCeIlQIAAExcfavZWTYnI97iSiJHaqCzjDGMAACcqZ0HmyVJF6zOJ/iZgAWFqXI67OroGVJDW5/V5QAIE4RlCFvlle2SpMXFhGUzLTc9XlmpsXJ7DO2vbAt8/KW99ZKks5bNOe3nx8e6AmEay94BAEAo6O0fVlfvsCQ6y6YTnWUAAEyN12uovNK/H55nYBMR5XJovm8HbXlF2+nfDAA+hGUIS739w6pq7JZkdjFhZtlsNq1ckCVJenG3GZA1tvXpYJW5aHbj0pxxP9/fXcbeMgAAEArqW81bx2lJMYqNZlr9dElNipYkdfUNyePxWlwNAADhp6a5Rz39I4qOcqgkP8XqcsKG/3mh/1kVAIyHsAxhqbyyXYYh5WXGKzUxxupyZqVNa/IlSc/vqlP/4IgefPqIJGnVgkylJ8eO+/knwjJuGQMAAOvVt/hGMGYygnE6JcdHy263yTCkzl5GMQIAMFn+yUplvtGCmJhSX2dZRV2XtYUACBv8FxZhac/RVknS0pIMiyuZvZYUpysvM0GDwx59+vtP6YlXqiRJV15cNqHP94/kISwDAAChoKmjX5KUk0ZYNp3sdptSEszuMkYxAgAwedUN5mSlUrrKJqUkL0WSdLyhW2662wFMAGEZwtJeX1i2vJSwzCo2m03//c6lstukjp4heQ3p4vWFWjLBHXL+7rO2bsYwAgAA6zW3m2eSrLQ4iyuJPGm+iQId3XSWAQAwWbXNZvd7QTY7VScjJz1O8TFOjbi9qmnqsbocAGGAYfwIOz39w6psMFuol9FZZqm1i7L1tY9v0LM7a1WUm6TLLyyd8Of6xzC201kGAABCQHO72VmWnTb+OGlMTppvbHobnWUAAExabbMZ9ORnJVpcSXix2WwqzkvR3mOtOlbbpXlzkq0uCUCIIyxD2Nl3rFWGYd6oSU1iX5nV1i/O0frFOZP+PHaWAQCAUOIfw5iVSmfZdEtNMscwdhCWAQAwKf2DI2r1PTfJy6KzbLJK8pPNsKyuU29SodXlAAhxjGFE2PHvK6OrLLylJ/nHMPLQBAAAWMvrNdTiD8sYwzjt/Ltq2VkGAMDk1Lf0SZJSEqKVGBdlcTXhpyTP7CY7VttlcSUAwgFhGcKOPyxbPj/T4kowFWmvG8NoGIbF1QAAgNmso2dQbo8hu92mdCYXTDv/NAh2lgEAMDm1Lea+MrrKzkxJfookqbK+Sx4vz54AnB5hGcJKR/egqhvNWc1Li9MtrgZT4b9h7PZ41d03bHE1AABgNmvy7SvLSI6Rw8FfkaZbWqI5hrG9e8DiSgAACC8ndqrS+X4m5mQmKDrKocFhj+p9wSMAjIW/CSJkHKnp0E2/fEk3/OwFbd1TP+p7XtnfKEmaX5Ci5ITomSwP08zltCs5wRwhwEgeAABgJf8O1Uz2lQVFYKIAnWUAAExKs29MdGZqrMWVhCeH3aZ5uUmSpGN1jGIEcHqEZQgJze39+tovXtTOQ83aX9Gm79+3TS/vazjlfS/5PnbWstyZLhFBENhb1kVYBgAArOM/i6QxgjEo/L+unb1DjEACAGASWjrNruwsLvScMf8oxmO1nZbWASD0EZYhJPzyb3s1MOTR3JxErVucLcOQfnj/Dh2u7gi8p717UHuOtEiSNi4lLIsE/lvGbV2M5AEAANbxd7kTlgVHSkK0bDbJ6zXU3Ud3GQAAE9Xi6yzLorPsjJXkJUuSKugsAzAOwjJYrq1rQK+Wm+MVv3zVWn3to+u1emGWhkc8+t5vt6mn39xn9egLFXJ7DC0qSlNBdqKVJWOapPtH8tBZBgAALNROZ1lQORx2JcebI9Q7GMUIAMCEGIah5g46y6bq9Z1lhkGHO4CxEZbBcs+9VifDkBYVpakwJ0kOh11fuWqtcjPi1do5oO/e+4p2HW7W35+vkCS964ISiyvGdElNNB9IdfTw0AQAAFjH31nmv8iD6ZeaZIZl7KoFAGBiuvuGNTTskSRlpNBZdqYKshPldNjVN+hWU3u/1eUACGGEZbDc1j31kqQLVucHPhYX49INH16n+Binyivb9Y27XtLQsEcr52cygjGC8NAEAACEgvZu89Z2GmFZ0KT6uvY49wEAMDEtvq6y1MRoRbkcFlcTvlxOu4pyzQlVx2oZxQhgbIRlsFT/4IgO13RKktYtyj7pteK8ZH33M+eoMMf8A23Vgkxdf9Va2e22mS4TQeLvLOukswwAAFgo0FnGGMagSScsAwBgUvz73dPpKpuywCjGuk5L6wAQ2pxWF4DZrbyyXV6vodz0eGWlnTp/uTQ/RT/90iZ19gwqPZnDQaQJdJb18NAEAABYo39wRAND5oijVMKyoPGPj2rtHLC4EgAAwkO772JxWiLnk6kqyUuWRGcZgNOjswyW2n2kRZK0fH7GmO9x2G0EZRHKf+Dr6B5iySoAALCEv9MpLsap2GjuEgaLPyxrISwDAGBCOnxnFMZET93rO8t4/gRgLIRlsNQR3wjGxfPSrC0ElkhJNDvL3B6v+gZGLK4GAADMRv6wLI2usqCiswwAgMkJnFF8z05w5ubmJslut6mrdziwCw4A3oiwDJbxeg1V1JntzyV5KdYWA0tEuRyKj3VJYn8FAACwRlsXYdlMyCQsAwBgUjq6zTGMjImeumiXQ/N93WX7KlqtLQZAyCIsg2Ua2/s0MOSWy2lXXlaC1eXAImm+vWUdvlncAAAAM6m9ixFHM8HfWdY/6Fb/IBMFAAAYT3u3ecGECz3TY2lJuiRpz1HCMgCjIyyDZfxdZXNzk+R08K/ibJXq31tGWAYAACzg725P50FUUMVGOwMTBdhbBgDA+NoDnWWMYZwOy0ozJEl7j7VZXAmAUEVCActU1ndLkornJFtcCawUCMsYwwgAACzQxs6yGeMfxdjWybkPAIDT8XgNdfaaYRlnlOmxeF667Habmtv71dTeb3U5AEIQYRksU9PUI0mam5NocSWwUipjGAEAgIX8YxjTk2MtriTy+UcxNnXwgAoAgNPp7huS12vIZpNSEugsmw6x0U7NL0iRJO1lFCOAURCWwTL+sCw/m7BsNktN9IVldJYBAAALtNNZNmNy0uIkSU1tfRZXAgBAaOv0XShOio+Sg9Ul02Z5YBQjYRmAU/FfW1jC7fGqodX8S3J+VoLF1cBKqUn+nWWEZQAAYGYZhnEiLEsmLAu27PR4SWL0EQAA4/CHZXSVTa+lJWZYtudIiwzDsLgaAKGGsAyWaGjtk8drKCbKEdhdgNkp0FnGGEYAADDDegdGNOL2SpLSkngYFWw56WZnWSNhGQAAp+XfV5aSyPlkOi0pTleUy6HWrkFV1ndbXQ6AEENYBkvUNvtGMGYlyGazWVwNrBToLGMMIwAAmGFtvn1liXFRcjkdFlcT+bIDYxgJywAAOJ0TnWV0vk+naJdDqxZkSpJe2d9ocTUAQg1hGSxR12KOYMzLZF/ZbJeaaB78evpHNOL2WFwNAACYTdp9YVk6IxhnhD8s6+kfVv/giMXVAAAQugJhGZ1l027DkhxJ0qv7GyyuBECoISyDJfx7CnIy4iyuBFZLjHPJ6TC7Czt7hi2uBgAAzCbt3QOSpLQkwrKZEBfjUlJ8lCSpke4yAADG5B/DmJwQZXElkWft4mzZbNLR2i61dg5YXQ6AEEJYBks0tpmdZTlp8RZXAqvZbDal+LrLOnoYxQgAAGZOm28MNGHZzMnNMM//9a29FlcCAEDo8odlqXSWTbvUxBiVFaZKkraVM4oRwAmEZbCEf0+Bf8k3Zjf/4Y+9ZQAAYCb5xzCmMYZxxuRnJUiSapoIywAAGMuJMYycUYJhw9JcSdLL7C0D8DqEZZhxHq+h5g5/WEZnGU7c5m73HQYBAABmQjudZTOuIMvcWVzb1GNxJQAAhK5AWJZAZ1kw+PeW7TnSor4B9qgCMBGWYca1dQ7I4zXkdNh5MAFJJxbWdtJZBgAAZhBh2czzd5bVNtNZBgDAaLxeQ12BnWWEZcFQkJ2o/KwEuT2Gth9osrocACGCsAwzrrHd3FeWnRYru91mcTUIBf4HVB10lgEAgBnkH8OYzhjGGVOQ7essa+mV12tYXA0AAKGnb3BEHt+fkSmJURZXE7nOWmaOYnxpX4PFlQAIFYRlmHGNvn1l2YxghI9/Z1k7nWUAAGCGeLxGYAQ0nWUzJzstTk6HXcMjnsBodgAAcIJ/BGN8rEsup8PiaiLXRt/esp0HmzQ84rG4GgChgLAMM66xzewsy0mLs7gShAr/wtpOOssAAMAM6ewZlNdryG47cXEHwedw2FXo6y6rrO+yuBoAAEIP+8pmxvyCFGUkx2hgyKNdR1qsLgdACCAsw4xr8nWW5dBZBp+0JPMA2NFDZxkAAJgZbb4RjCmJMXI4+GvRTCrOS5YkHaslLAMA4I0CYRmXeYLKZrMFuste3ssoRgCEZbBAU7tvDCOdZfBJ9XWWtXcPyTDYXQEAAILPH5ZlpDCCcaYFwrI6wjIAAN6os5fOspmy0be37JX9jfJ4vBZXA8BqhGWYcY3tvjGMdJbBJ9XXWeb2eNU3MGJxNQAAYDZo7xqQJKUnx1pcyexTkm+GZRWEZQAAnCIQltFZFnRLitOVEOtSd9+wyo+3W10OAIsRlmFG9Q+OqKt3WBKdZTjB5XQoIdYlSWrvZhQjAAAIvlZfZ1l6Ep1lM23enGTZbea5r80XWgIAABNjGGeO02HX+iU5khjFCICwDDPMP4IxMS5K8b5wBJCk9GTzQZX/wRUAAEAw+UOa9BQ6y2ZabLQzMIpx77E2i6sBACC0BMIyxjDOCP/espf2NbAaBJjlCMswo1o6zYcSWWk8lMDJ/A+q2jq5XQwAAILPv7PMf2EHM2tpSYYkad+xVosrAQAgtHT5xjAmE5bNiFVlmYpyOdTSMaAjNZ1WlwPAQoRlmFGtviAkg90QeAP/vxN0lgEAgJkQ6CwjLLPEMl9YtvcoYRkAAK/X4QvLUhnDOCNiopw6y9dd9o/nKyyuBoCVCMswo/xhWSbjbvAGGb4HVeytAAAAwWYYxus6yziXWmFJcbocdpvqW/tU39prdTkAAIQEwzDYWWaBd11QIkl6bledapt75PUaenxrpa790TP60u3Pas/RFosrBDATCMswo/xjGDMIy/AG/jGMrYxhBAAAQdY/6NbgsEeSlJ5EZ5kV4mNdWlKcLkl6dX+TxdUAABAaBobcGh4xzyiEZTOntCBFaxdly+s19O27X9aNP39Bv/jrHh1v6Nbh6k59555XVNXQbXWZAIKMsAwzqpWwDGPwj2FsYwwjAAAIslZfJ3t8rEsx0U6Lq5m91i/JkSS9ur/R4koAAAgN7d3mM5G4GKdiojijzKTPvGe54mKcamzrV3llu6Kcdn34bYtUVpiqwWGP/vLUYatLBBBkhGWYUYRlGEt6inmrm84yAAAQbCdGMNJVZqWNvv0g+ypaGcUNAICkjh72lVklKzVOt/7P+brkrCK97ewi/fiLF+iKixbo0+9ZLkl6cXd9IMwEEJkIyzBjvF5DrZ3mHyqEZXgjf2dZ78CIBofcFlcDAAAiWbsvmMlgX5mlstPitHhemgxDenZnndXlAABguc5u/74yLvRYIT8rUde8d4U+854VmpuTJEkqzU9R2dxUebyGXtrbYHGFAIKJsAwzpqtvSG6PVzYbt3hxqvhYl+JjzBEDTR39FlcDAAAiGZ1loePCNQWSpP+8clxer2FxNQAAWKujxzyjpLFTNaSsW5QtSdpztMXiSgAEE2EZZox/vF5qYrScDv7Vw6my0+IlSU3thGUAACB4Wn1hWRphmeUuWJWnuBin6lr6tPNQs9XlAABgKf+YP8YwhpYV8zMlSXuPtnK5B4hgJBaYMYxgxHiy0+MkSU1thGUAACB42hjDGDLiYlx684a5kqS/P3fM4moAALCWf2dZCmFZSCktSFFstEM9/SM63tBtdTkAgoSwDDPG31lGWIaxZKf5wjI6ywAAQBC1dHAuDSWXnjNPdpv02uEWVTXyAAoAMHt1+sIyxjCGFqfDrgWFqZKkIzWd1hYDIGgIyzBjCMswnhNhWZ/FlQAAgEhlGIaafftR/WcPWCsnPV4bluZKkv62he4yAMDs5d9ZlppIWBZqSvJSJEkVdZ2W1gEgeAjLMGP8YVkmYRnGQGcZAAAItt6BEfUPuiVJWYRlIePyTaWSpGd21ATCTAAAZpuObrOzLDWJMYyhpiQ/WZJ0rK7L4koABAthGWZMC51lGIc/LGts65dhsDAVAABMP/+lnJTEaEW7HBZXA7+Fc9O0vDRDHq+hh585anU5AADMOI/Hq64+dpaFqpL8FElSZX23PB6vtcUACArCMsyY1i7CMpxebka87DZpYMgdWGoLAAAwnZp9YVl2Kl1loeZ9b1ogSfrPK1WBMVQAAMwWXX3DMgzJbrcpKZ6wLNTkpscrJsqh4RGP6ltZHwJEIsIyzAiP11B7l/kX3oxkwjKMzuV0KCc9XpJU09hjcTUAACAS+Uf8MYIx9CwvzVBZYaqG3V498iy7ywAAs0tHt/ncLCUhSg67zeJq8EZ2u00F2YmSpOomnlkBkYiwDDOis2dQHq8hu92m1CSWlGJs/oNHTTMHDwAAMP2a2nxhWSoXuEKNzWYLdJc9vrVSXb1MGgAAzB7+CTspiTw3C1WBZ1aEZUBEIizDjGjzdZWlJUZzOwanlZ+VIImDBwAACI6GNnNsTravmx2hZd3ibBXPSdbAkEe/ebTc6nIAAJgx/s6yVPaVhay5Ob6wjGlIQEQiLMOMaPPtK0tnXxnGUeg7eNQ291pcCQAAiET+HRN5mYRlochms+nTly+XJD25rVqv7m+0uCIAAGaGv7MsjYlMIYsxjEBkIyzDjGjtZF8ZJqYwO0mSVFHXJa/XsLgaAAAQSdwer5razTGMeZkJFleDsSyal6Z3nF8sSfrR77fr3y9Xqb17UC0dA6pr6dXgsNviCgEAmH4dPb6dZXSWhSx/WFbb3CuPx2txNQCmm9PqAjA7BDrLkrkdg9MrmpOkKJdDvQMjqmvpDRxEAAAApqqpvV9er6HoKAe3tkPcRy9drOP13dpztFV3PrDrpNeiXA599NLFuuy8YmuKAwAgCDq6zc6yVHaWhays1DhFRzk0NOxRY3s/l6+ACENnGWaEv7Msnc4yjMPpsGtBYYok6cDxdmuLAQAAEaWuxRzzPCcjXjYbe3RDmcvp0Lc/eZY+/LZFysuMl80mOR02RTntGh7x6Jd/26stO2utLhMAgGnjv2jOhZ7QZbfbVJBlBmTV7C0DIg6dZZgRrb4/8DNS+AMf41tUlKZ9x9p0oLJdb94w1+pyAABAhKhvMfeVzcngFnA4cDrsuuKiBbriogXyeA3Zffnmbx8r11+fOapf/W2v1i3KVnysy9pCAQCYBq1dvhUmPDsLaQXZiTpa26Waph6dtSzX6nIATCM6yzAjToxhpLMM41takiFJ2n6g6aQZ0IZh6MXd9fr5g7t1/78OqNm3cwQAAGAianzL2POyCMvCjcNuk81m/vPBt5rdZt19w9qyo8bq0gAAmDKP11B7tz8s49lZKPOvC/GfKwFEDsIyBJ1hGGrr4g98TNzy0gwlxUeps3dIu4+0SpI8Hq9+/Ied+v592/TPl47rz08c1hdve1bHG7otrhYAAISLKt+5oSg3yeJKMBUup12XnmPuK/vnS8dlGIbFFQEAMDUd3YPyeg057DalsLMspBX6wjLGMAKRh7AMQdfdN6wRt9kdxNxlTITTYdd5K/MkSX9//pjcHq9++pdd2rKzVg67TZecVaTCnER19w3rh/dvP6n7DAAAYDRer6HjjYRlkWLT2gK5nHZVNfaompvdAIAw19rpn8gUI4edvaqhrCDHDMtqm3vk9XJhB4gkhGUIOn9XWUpCtFxO/pXDxFx6zjw5HTbtONisK258TE9vr5HdJn35qrW65r0r9L1rzlVinEvVjT16clu11eUCAIAQ19jep6Fhj1xOu+ZkxFtdDqYoIdalFfMzJUmv7m+0uBoAAKampZP1JeEiOzVOToddw25v4PcNQGQguUDQtfr3lbGgFJNQkJ2oD751kSTJ7fEqPsapr31sg85ePkeSlBQfpfe9qUyS9OgLlYzfAQAAp+UfwViYkyiHg78GRYL1i7MlEZYBAMKfv7Msk/UlIc/hsGtOpnnxqq651+JqAEwnp9UFIPK1+f7Az+B2DCbpvZvna+X8TNW39mr1wmwlxLpOev1N6wp03+PlOt7QrWO1XSotSLGmUAAAEPKO1HRKkublJltbCKbN2kU5kvbocHWH+gdHFBfjGvdzAAAIRf6wLIOwLCzkZyWourFHtc09Wr0wy+pyAEwTrlQi6Fp9YxjTk+ksw+SVFqTo/FX5pwRlkpQQF6WNS3MlSc/srJnp0gAAQBg5eLxDkrSwKM3iSjBdMlNjlZUWJ68hHarqsLocAADOWFN7vyTzzzaEvrzMBElSLZ1lQEQhLEPQcTsGwXTuCnMs4yv7GhnFCAAARuX2eHW4xgxTFhWlWlwNptNiX/hZXtlucSUAAJy5xrY+SVJOOntVw0F+VqIkwjIg0hCWIejaA51lhGWYfqvLshTltKupvV/HfbtIAAAAXu94fbeGhj2Kj3UFHm4gMiyeZ4ZlB463WVwJAABnxjAMNfo6y3IzCMvCQX6Wv7Osx+JKAEwnwjIEXWuX2VnGGEYEQ0y0UysXmPOhdxxstrgaAAAQivYea5UkLSpKk91us7gaTKeyuWZYdrSmkykDAICw1NkzpKFhj2w2KSs1zupyMAH+sKyjZ0i9AyMWVwNguhCWIagMw2AMI4JuxfwMSdI+34MwAACA19t1uEWStGJ+psWVYLoVZCfK6bCpb9Ct5o4Bq8sBAGDSGtvMrrKMlFi5nDyqDQdxMS6lJUVLkuroLgMiBv8FRlD1D7o1OOyRJKUn0VmG4FhaYoZl5ZVt8ni8FlcDAABCyfCIR/sqzBF9qxYQlkUal9OuwpwkSVJFXZfF1QAAMHkNvn1luewrCyv+0d51LewtAyIFYRmCyj+CMSHWpZhop8XVIFIV5SYpIdalgSGPjvGQBAAAvM7uIy0aHvEoLSlahTnsK4tExXOSJRGWAQDCU6MvLMshLAsreYG9ZYRlQKQgLENQtXUOSmIEI4LLbrdpSXG6JEYxAgCAkz21vUaSdO6KPNls7CuLRPPyzM6yynrCMgBA+KluMsf4+fdgITzkZ5q/XzVNjGEEIgVhGYKqzddZlp7MCEYE17JScxTj3mNtFlcCAABCRW//sF7Z1yhJ2ry2wOJqECyBzjLCMgBAGKpu7JYkOuDDjP/3q6qRsAyIFIRlCKrWLrOzLD2ZzjIE11JfZ9n+CvaWAQAA0/O76uT2eFWUm6TivGSry0GQzPOFZS0dA+rpH7a4GgAAJm7E7VV9izmGsTA7yeJqMBlzc83fr8a2Pg0OuS2uBsB0ICxDUPk7yzLoLEOQFc1JVnysSwNDblXWd1tdDgAACAH+EYwXrStgBGMEi491KTstThKjGAEA4aW+pVcer6G4GKcyUnh2Fk5SE2OUnBAlwzgxShNAeCMsQ1C1dPrGMLKzDEHmsNu0oCBFknSkpsPaYgAAgOVqm3t0qKpDdrtNF6zOt7ocBJm/c7CijktTAIDwUeUbwViQncjFnjA0N8fsLqtq4PwBRALCMgRVU1u/JCk7Nc7iSjAbLChMlSQdru60thAAAGC5p31dZavLspSayE3tSOcfxUhnGQAgnByrNf/c8v85hvBSNMcMy44TlgERgbAMQWMYhlo6fGFZOmEZgi8QltFZBgDArObxGnrmdSMYEfmKfHtD/Df0AQAIB0dqOiVJ832TchBein0h57E6LusAkYCwDEHT0TOkYbdXdpuUwRhGzAD/4bKmqUf9gyPWFgMAACyz92iLWrsGlRDr0vrFOVaXgxkwNzdRklTT2COP17C4GgAAxuf1Gjpa2ymJsCxclfp+3yrqOjl/ABGAsAxB09xudpWlp8TK6eBfNQRfalKMMlJiZRjc6gEAYDZ7ytdVdt6qPEW5HBZXg5mQnRavKJdDw26vGtv6rC4HAIBx1bX0amDIrSiXQ4XZiVaXgzOQn5Wo6CiHBoY8qm/ptbocAFNEgoGgafSFZVnsK8MMWlCYIkk6Us0oRgAAZqP+wRFt3dMgSbpoLSMYZwuH3abC7ARJUhV7QwAAYWBfRZsks6vMwSXzsOSw2wKjGP0jNQGEL/5LjKBpajdvdGanEZZh5swv8O0tq+60thAAAGCJF3fXa3jEo7zMhMA+U8wOcwN7y3osrgQAgPFtL2+SJK0uy7K4EkyF/7x58Hi7xZUAmCrCMgRNc/uAJCmHsAwzKNBZVkNnGQAAs9HTO8wRjBetK5DNZrO4GsykuTn+sIzOMgBAaBse8Wj30RZJ0tpF2RZXg6lYWpIuSdpztNXiSgBMFWEZgsbfWZZFWIYZVJqfIptNau4YUEfPoNXlAACAGdTU3q99x9pks0mb1jCCcbbxh2XVhGUAgBC371ibhoY9SkuK0bw5SVaXgylYWpIhu83cQdfWNWB1OQCmgLAMQePvLGMMI2ZSXIxL+VnmYlzmRQMAMLs84+sqW1GaqYyUWIurwUybm2ueAeta+jTi9lhcDQAAY9t+0BzBuHZRNp3wYS4h1qXiPHNv2V66y4CwRliGoPB4DbV09kuSstPiLa4Gs838ghRJ0uFqRjECADBbGIahp7ebYdmmtXSVzUZpSTGKj3XJ6zVU29xrdTkAAIzKMIzAvjJGMEaGZaWZkhjFCIQ7wjIERVvXgNweQ06HTWnJMVaXg1nGv1yVzjIAAGaPQ1UdamjtU0yUQ2cty7W6HFjAZrOpKNe3t6yBUYwAgNBU19KrhrY+OR02rZifYXU5mAbLS83fR8IyILwRliEomtvNrrLMlDg57LSTY2b5O8uOVHfIMAxriwEAADPi2Z21kqSzluUqNtppcTWwSmGOOYqxqrHH4koAABjd9gPNkqSlxRmKi3FZXA2mw+J5abLbbWpq71eT75kogPBDWIag8P/BkJXGrgjMvHlzkuR02NXTP8IhBQCAWcDrNbR1b70k6byVeRZXAyvNzfF1ljXSWQYACE3bDzRKktYuZgRjpIiLcanMN+Vo+4Emi6sBcKYIyxAUjW3sK4N1XE6H5s0xH5SwtwwAgMh3qKpD7d1DiotxauWCTKvLgYXm0lkGAAhh/YMj2l/RJol9ZZFm41JzDPjWPfUWVwLgTBGWIShqms2/nOZnJVhcCWYr9pYBADB7vOh7KLF+SY5cTofF1cBKhb7Osub2fvUPjlhcDQAAJ9t9pEVuj6HcjHjlZfLMLJKcvdwMy/Yda1Vnz5DF1QA4E4RlCIqaJjMsK8hOtLgSzFb+vWV0lgEAENkMwwiEZecsn2NxNbBaUnyU0pKiJUnVTXSXAQBCy7Zyc0QfXWWRJyc9XqX5yfIa0sv7GqwuB8AZICzDtPN4vKpv6ZVEWAbr+MOyY3Vd8ni81hYDAACC5khNp1o7BxQT5dCqsiyry0EIKMpNliRV1nVZXAkAACcYhqEdBwnLItnZvotbLzKKEQhLhGWYdg1tfXJ7DEVHOZSZEmt1OZil8rISFRvt1NCwRzXNvVaXAwAAgsS/F2Ld4hxFuxjBCKkk3wzLjtYSlgEAQkdFXZfau4cUHeXQspJ0q8tBEJyzwgzL9hxlFCMQjgjLMO1qmsxgIj8rQXa7zeJqMFs57DaV5qdIYhQjAACRihGMGI3/DHiU3bUAgBCy3ddVtnJ+JjtWI9ScjASVFqTI6zX03Gu1VpcDYJIIyzDtKuvNG5xzfcu1AassKEyRZI5nAgAAked4Q7ca2/oV5XJozUJGMMJU6hvHXdXYreERj7XFAADgs519ZbPCRWsLJElPba+xuBIAk0VYhml3tLZT0okbnYBV5hekSqKzDACASPVqeaMk84Z2TLTT4moQKjJTYpWcECWP19Dxhm6rywEAQF29QzrkezaxZiFhWSQ7b2We7HabKuq61NjWZ3U5ACaBsAzTzj/uhLAMVpvvv1XcwK1iAAAikf+G9rrFPHTCCTabTSW+v4swYQAAEApeO9Qsw5CKcpOUmRprdTkIouSEaC0tNnfSvbyv0eJqAEwGYRmmVVvXgDp6hmS3SfPyGMMIa2WmxiolIVoer6GKeha8AwAQSV5/Q5txRnij+b6w7Jhv6gUAAFbaxgWfWWXD0hxJ0sv7GiyuBMBkEJZhWh08bj6wKMhOVEwUo3BgLZvNFthZwShGAAAiy46D5g3teXOSlJHCDW2cjM4yAECoGHF7tO2AGZatX5xjcTWYCf7f54PH2zUw5La4GgATRViGabXjoPmH/4oFmRZXApgWFJp7y3hQAgBAZNl+wH9Dm4dOOJV/HHd1U4+GGMcNALDQ7iOtGhhyKy0pJvCMApEtJz1eWWlx8ngNlVe2WV0OgAkiLMOk9Q2M6Ght5yk7oAzDCDy0WMuyUoQI/4OSI3SWAQAQMdwer3YeapYkrWMEI0aRnhyjlIRoeb2GKhnHDQCw0NY99ZKks5blym63WVwNZsqK0gxJ0p4jrRZXAmCiCMswKTsPNuuj//ff+uJPntVn/t9T2l9x4nbEvoo2dfQMKSbKoaUl6RZWCZzgD8vqWvrUOzBibTEAAGBaHDjerr6BESXFR2k+N7QxiteP4z7KhAEAgEU8Hq9e2d8oyQzLMHss94Vle48RlgHhgrAME9baOaD/97ttGhw2O8qaOwb0jbu26qW95g2ZB58+Ikm6cE2BXE6HZXUCr5ecEK3stDhJ0jEelAAAEBG2l5vTDNYszJKDG9oYQ6lvb9nR2k5L6wAAzF7lle3q7htWYpxLS4u5WD6bLCxKkyRV1nedMp0LQGgiLMOEPfLcMfUPujW/IEV//O7btGFJjkbcXn3vt9t0zQ+e0s6DzbLbpMsvLLW6VOAk/pngB6vaLa4EAABMh20HzBva6xaxrwxjK81PlkRnGQDAOlt21kqSNizJlcPBY9jZJDstTikJ0XJ7DFXUMRIaCAf8VxoT0j84on+/XCVJ+q+3LFRCrEs3fmSdLjm7SIYh1TT1SpI++vYlys2It7JU4BRL5pm3efYdY6kqAADhrq6lVzVNvXLYbVq1MMvqchDC/GMYa5p6NDDktrYYAMCsMzDk1vO7zLDsonUFFleDmWaz2VQ21395u8PiagBMhNPqAhAedh1u0cCQW7np8VrjeyjhcNh1zXtWaPOaAu2raNO8OUlas5AF6wg9S31zosuPt2vE7WFMKAAAYezlvQ2SzD0QCbEui6tBKEtPjlVGcoxauwZ1tKZTy3xnQgAAZsJ/XqnSwJBHczLitYQRjLNS2dxUvbK/UYeq2iWVWF0OgHHQWYYJ2ebbC7F+SY5stpP3QiwsStN7N88nKEPIKsxOVHJClIZHPDpc3Wl1OQAAYApe3meGZRuX5VpcCcJBmW9fCOO4AQAzqat3SH9+4pAk6V0Xlp7yLA2zg7+z7FA1nWVAOCAsw7i8XkPbD5hh2brFBGIIPzabTUtLzJvE+461WlwNAAA4U+3dg4GHDRuWsK8M41voH390nIdUAICZ0ds/rO/e+4p6+kdUmJOoN68vtLokWKQ0P0V2m9TSMaC2rgGrywEwDsIyjKu+tVedvUOKctq1eB5t4whPy3xh2Z6jhGUAAISrV/Y3yjCkssJUpSfHWl0OwsDCuWZn2aHqdhmGYXE1AIBIt/doq77wk2d1sKpD8bEu3fDhdXI4ePw6W8XFuFSYkyRJOkx3GRDy+K81xnXIt4SytCBFLif/yiA8LfftqDjo21sGAADCz4u76yRJG5bSVYaJKclPltNhV1fvsBrb+q0uBwAQwZ7aVq2v37VVTe39ykqL0y2fOUcF2YlWlwWLBUYxVhGWAaGO5APj8o+6WVCYanElwJnLz0pQSmK0ht1elVeyswIAgHDT0jEQ6BA/f1W+xdUgXLicDpXkJUtibxkAIHjKK9t0x192yes1dOGafN3xpQtV7PvzB7Ob/3nqkZpOawsBMC7CMozL3ybsH2EChCObzaa1C82dey/vbbC4GgAAMFlbdtbIMKSlJenKTouzuhyEkbIibnQDAILH4zV0x192yeM1dP7KPF33gdWKi3FZXRZCxPyCFElmWOb1MhIaCGWEZTgtt8erqoZuSeYYRiCcnb08V5K0dW8DBxQAAMKIYRh6enuNJOmitQUWV4Nw47/0R2cZACAYnn+tVrXNvUqIdema966QzWazuiSEkMLsREW5HBoYcquupdfqcgCcBmEZTqu+pVduj6HYaKeyUlmijvC2ckGmYqOdau8e1OEabhYDABAujtR0qra5V1Euh85ePsfqchBm/LtCKuu7NTjstrgaAECk+ccLFZKkd11YovhYOspwMofDrtJ8cyTnEZ5FASGNsAynVdXYI0kqzEnkZgzCnsvp0LrF5ijGrXsYxQgAQLh45LljkqSzl+Uy1giTlpkSq7SkGHm9ho6yLwQAMI2qG7t1uLpTdrtNb94w1+pyEKLmF5gXdw5Xd1pbCIDTIizDaVU1miMY5+YkWVwJMD38t9G37qmXYTCKEQCAUFfT1KPnd9VJkt59YanF1SAc2Ww2LfTtLTvI3jIAwDTasrNWkrRuUbZSE2MsrgahakFhiiQ6y4BQR1iG06r2dZbNzUm0uBJgeqwpy1JMlENN7f3aV9FmdTkAAGAc9/5jvwxD2rg0R8V5yVaXgzBVVmjuLTvE3jIAwDTafqBJknTOCsZEY2z+zrKKum6NuL0WVwNgLIRlOK2qBjrLEFliop26YHW+JOlfW49bWwwAADitLTtrtf1Ak5wOmz769iVWl4Mw9vrOMqYLAACmQ1vXgCrru2WzSavLsqwuByEsJz1OiXEuuT1eHW/osrocAGMgLMOYhkY8amjrkyQV5tJZhshxyVlFkqSte+vV2TNkbTEAAGBUFXVd+tkDuyRJV1y0QHmZCdYWhLBWkp8ip8Omzp4hNbX3W10OACAC7DjYLElaUJCq5IRoi6tBKLPZbIHusiPsTwVCFmEZxlTT1CPDkJLio5TCH/qIICX5KVpQmCK3x9ATr1ZZXQ4AAHiDtq4B/d97XtbgsEcrF2TqyovLrC4JYS7a5dC8OeYYz0PsLQMATAP/CMY1C+kqw/jmF6RIko5Ud1paB4CxEZZhTNWNJ0Yw2mw2i6sBptclZ82TJD2+9TjzogEACCFuj1c3//pVtXUNqiA7QV/58Do57JxFMXULi8y9ZQfZWwYAmKIRt1e7DrdIktYsyra4GoQDf1h2uIZLO0CoIizDmKoaeiRJhTmMYETkOX9VnlISo9XaOaBnd9ZaXQ4AAPD50xOHdKSmUwmxLn3zExuVEOuyuiREiLJCc/zR4WoeUgEApubg8XYNDLmVnBCl0vwUq8tBGJjvO4fUNvVoYMhtcTUARkNYhjFVNxGWIXJFuRx69wUlkqQHnz4ij5dF7wAAWO1QVbseeOqIJOma965QTnq8xRUhkpTNNR9SVdR1aXjEY3E1AIBw5h/BuLosS3Y64DEBaUkxykiJldfg4g4QqgjLMKb6ll5JYpk6ItZbzypSfKxLdS29enlvg9XlAAAwq3m8hu58YLe8XkPnr8rTeSvzrC4JESY7LU4pCdFyewxV1HVZXQ4AIIztOGiGZWsZwYhJWFqcLknac7TV4koAjIawDKPyeA01d/RLknK50YsIFRfj0tvPNXeXPfD0YRkG3WUAAFjl6W3VOt7QrfhYlz717uVWl4MIZLPZtMA3AukQN7oBAGeouaNfVY09stukVWVZVpeDMLJifqYkabdv3x2A0EJYhlG1dg7I7THkdNiVnhJrdTlA0Fx2brGioxw6Vtul1w5xWAEAwAper6EHnzbHL77vogVKio+yuCJEKv8oxkNVhGUAgDOzwzeCsWxumhLjOLNg4vxh2ZGaDvX2D1tcDYA3IizDqBpazRGM2WlxcjB7GREsOSFab91YJEn6y1OHrS0GAIBZavuBJtW39ik+1qVLzi6yuhxEsDJ/Z1lVu8WVAADC1fYDzZIYwYjJy0yNVVFukryG9BLrQICQQ1iGUTW0+UYwZjCCEZHv3ReWyOmwaX9Fm/ZXtFldDgAAs85/XqmSJL15w1zFRjstrgaRbH5himw2qbljQB3dg1aXAwAIM8MjHu0+ak6lWbeYsAyT59/L+9xrdRZXAuCNCMswqobWPkmEZZgd0pNjtXltoSTpr88csbgaAABml+6+Ye04aI4zumhdgcXVINLFxbhUmJ0oib1lAIDJ23usVUPDHqUnx6goN8nqchCGzl9lhmV7jraonYs7QEghLMOoGtvMsCwnPc7iSoCZcfmmUtls0rbyJlU1dFtdDgAAs8aLu+vk9hgqnpOsuTk8dELwLShkbxkA4MxsLzcv+KxdlC2bjbUlmLyc9HgtnJsqryG9sIvuMiCUEJZhVP7OsjkZCRZXAsyMvMwEnbUsV5L00JajFlcDAMDs8cyOWknShWvyLa4Es0XZ3DRJ0mE6ywAAk2AYhrYfPBGWAWfqgtXmufeZnbUyDMPiagD4EZbhFIZh0FmGWek9m+ZLkp7dWavmjn6LqwEAIPI1tvXpwPF22WwnRtIAwbZwrtlZdri6Qx4vD6gAABNT3dijxrZ+uZx2rZifaXU5CGPnrsiT02HX0ZpO7atos7ocAD6EZThFZ8+QBoc9stuk7DTCMsweCwpTtbw0Qx6voUeeO2Z1OQAARLyX9jZIkpaVZCg9OdbiajBb5GcnKjbaocFhj6obGb8NAJiYl/eZ55YV8zMVG+20uBqEs5TEaF28vlCS9JcnD1tcDQA/wjKcot43gjEjJVYup8PiaoCZ5e8u+8/LVerqHbK4GgAAItur5Y2SpA1LcyyuBLOJw25TWaE5irGc29wAgAl6yReW+Vc4AFPxns3zZbfbtOtwC6OhgRBBWIZTnBjBGG9xJcDMW1WWqdL8ZA0Oe/TXZ9hdBgBAsPT0D6u8sl2StH4xYRlm1tLSdEnS3mOEZQCA8TW39+tYbZfsNs4tmB7ZaXHa5NvZ+6cnDllcDQCJsAyjaPCFZbkZhGWYfWw2mz741kWSpH88X6HjDYzmAQAgGHYcaJLXa6gwJ5FLWphxy0oyJEl7j7XKMCa2t2zE7dUjzx3TD+/frhd31wezPABAiHl5v9lVtmheulISoy2uBpHiiosWyG6TtpU30V0GhADCMpyiwTeGMZeHFpil1izM0tpF2XJ7vPr+b19Ve/dg4DWPx6sXd9frnr/v032Pl6u8ktvIAACciVfLmyRJG5ZwOxszb35BqqJcDnX3DauqsWfc93u9hm79ww7d/cg+Pfdanb5/3zb9c2vlDFQKAAgF/j2rGxkdjWmUl5mgC9cUSJL+8O+DFlcDgLAMp2iks2zKvF6v7rnnHl188cVatmyZLrnkEt1///2n/Zwnn3xSZWVleuWVV076+BNPPKGLLrpIGzZs0M033yyPx3PS69/73vf09a9/fUJ13XDDDdq8efOYr2/evFk33HBD4MdXXXWVysrKAv8sXLhQq1at0uWXX6777rtPbrf7pM+/4447VFZWNqFaQpnNZtPnr1ypjJRY1bX06Qs/3qI//vugfvtYuf77lif1/fu26W/PHtMDTx3RV+58Qbf9aac83ondSAYAAJLb49XOg2ZYFu6jjDj3hSeX067lpWZ32Y4DTeO+/4lXq/Ti7no5HTYtKEyRJP3unwfU2z8czDIBACGguaNf+3xje89eNsfiaqYfZxlrvf/iMtntNu042KyDx9utLgeY1ZxWF4DQE+gsIyw7Y9///vf129/+Vu9///t18cUXq7q6Wrfffrtqa2tP+oPcr6OjQzfddNMpH29vb9f111+vj3zkI1q2bJm+8Y1vqKSkRO9///slSbW1tXrooYf06KOPBu3nsnjx4kBtHo9HXV1deu655/S9731P27dv12233Sa7PfJy99TEGH3vmnP07btfVm1zr/7wnxPzo5MTonTeijz1Dozouddq9dS2GiXFR+vjly2xsGIAAMLH/oo29Q26lZwQpfmFqVaXMyWc+8LX2oVZ2n6gSdsONOk9m+eP+b7+wRHd/0/ztvdHLl2iy86dp8//eIuqG3v0n1eqdfmm0pkqGQBggedeq5MkLSlOV1ZanMXVTD/OMtbKzYjXRWsL9MSr1fr9vw/qO5862+qSgFmLsAwn6R0YUU//iCSxO+IMtbe36/7779cVV1yhb3/724GP5+bm6pprrtEVV1yhkpKSkz7n29/+tpzOU//vuHPnTjkcDn3hC1+QzWbTyy+/rK1btwYOGrfddpuuvPJKZWdnB+3nk5CQoJUrV570sc2bN6u4uFg333yzHn30Ub3jHe8I2ve3Uk56vG6/7kI9tb1GB4+3y26zacWCTJ29LFdRLock8zb8D+7frr89e1Qbl+Zo8bx0i6sGACD0vbq/UZK0blGOHHabxdWcOc594W3Nomzp4b06cLxdXb1DSk4YfQfNg08fUWfvkOZkxOvSc+bJ4bDr0nPm6Rd/3aPnd9cRlgFABDMMQ8/sqJEkbfKNy4sknGVCw/vetEBPb6/RrsMtKq9s49kSYJHQitJhuUZfV1lKYrRio8lSz8Tx48fl8Xi0adOmkz6+YcMGeb1ePf/88yd9/PHHH9fWrVt1/fXXn/K1bDaboqKiZLOZD5FcLpe8Xq8kqby8XM8//7w++clPBulncnof+tCHlJ2drT/96U+WfP+ZEuVy6JKzivTFD6zW/7x/lS5cnR8IyiTpvFV5unh9oQxDuvcf+ye8IB4AgNnKMAy9Wm6GZeuXBO9hyUzg3BfectLjVZKfLK/X0Au76kZ9T1N7v/727DFJ0scuWyKX0/wr9FnLcmW3SUdrOgNj7AEAked4Q7eqG3vkdNh1zorIG8HIWSY05KTH603rCyWxuwywEmEZThIYwUhX2RlLTTVHCdXX15/08erqaklm27lfa2urvv3tb+urX/2qMjMzT/laS5cuVU9Pj5588kk1NTVpy5YtWrNmjSTphz/8oa6++molJSVNuka32z3qP5Nht9t11llnac+ePZP+3Ehz1SWLFOW061BVh3YfabG6HAAAQtqxui41tvUryuXQygVZVpczJZz7wp+/S+DJ7TWjvn7vP/ZpxO3V8tIMbVhyYr9eamKMFhebt753HmoOfqEAAEs8uc38M339kmwlxLosrmb6cZYJHe+7aIGcDpt2H2nl2RJgEcIynKShjX1lUzVv3jytWbNGd9xxh5544gn19PSovLxcX/va1xQVFaX+/v7Ae7/xjW9o1apVete73jXq18rOzta3vvUtffnLX9amTZu0cOFCffCDH9QLL7ygiooKXXXVVXrwwQd12WWX6aqrrlJ5efm49dXV1WnJkiWj/lNXN/qN2rFkZGRoZGREnZ2dk/q8SJOaFKM3b5wrSfrH85UWVwMAQGjzd/CsW5Qd9pMMOPeFv/NX5cnpsOtoTaf2HWs96bU9R1u0dU+D7Dbp6nctC9yU91sxP9P3vpM/DwAQGfoHR/Tkq2ZodPH6uRZXExycZUJHVlqc3rqxSJJ09yP75PZ4rS0ImIXC+2+nmHb+zjL2lU3NT3/6U33zm9/U5z73OUlSUlKSrr/+et1xxx2KjY2VJD388MPasWPHuItN3/ve9+ryyy/XyMiIoqOj5fV69aMf/Uif+9znVFlZqZtvvlm//OUvVV5erk9/+tN68sknFRUVNebXy8zM1C9+8YtRX/vMZz4zqZ+nf+TgGx8czEZvO3ueHn2hUtsPNKq1c0AZKbFWlwQAQMgxDEPP+8Ky81bmWVzN9ODcF95SE2P0pvWF+tdLx/X7fx/ULZ85RzabTf2DI/r5g3skSZecPU9FuafehF9WkiFJ2nesVYZhRNyvDQDMdk+8Wq3+QbfyMuO1uiy8u+FPh7NM6PjAWxZqy85aHW/o1s8e2K1r3rsiMAIaQPARluEkdJZNj4yMDP385z9Xd3e3mpubVVhYKLvdrptuuknJyclqbGzUzTffrBtuuEFpaWlyu92BOc5er1cej0cOx4m9WHa7XdHR5sLxv//97xoeHtbll1+uO++8U2vXrtW6deu0Zs0a3Xbbbdq1a5fWr18/Zm1RUVFatmzZmK9NRlNTk2JiYpSSkjKpz4tEBdmJWlqSrn3H2vTMjhpdcdECq0sCACDkHKruUHPHgGKiHFqzKDIeOnHuC39XbJ6vp7fXaN+xNj285aguWleoH92/Q3UtvUpLitF/vWXhqJ+3oDBFUS6HunqHVdvcq4LsxBmuHAAQLIPDbv316SOSpHddUCq7PXQDlqniLBM6kuKj9MUPrNZ3f/2KntxWrR0Hm1SSn6Ki3CRdvKFQczISrC4RiGhE0ziJfzl1bnqcxZWEt8cee0wHDx5UUlKSSktLFRUVpQMHDsjr9Wrx4sXaunWrenp69LWvfS3QPv7Rj35UkvTRj35UF1988ahfd3h4WD/96U913XXXyeFwqK2tTcnJyZLMw0hCQoJaW2dmDIzb7dYrr7yi1atXn3Qoms0uXJ0vSXpxT/047wQAYHbyd5VtWJKrmKjIuLfHuS/8ZaXF6SOXLpIk/frRcn3opn9p15EWRbkcuvEj65QUP/rDOJfToZI88/fkSE3nTJULAJgBDzx1RB09Q8pKi9NF6wqtLieoOMuElvVLcnTDh83zR0fPkLYfaNKDTx/RtT/aolfLG60uD4hokfE3VEyLoRGP2roGJUm53FSYkl/84hdasGCBfvzjHwc+9pvf/EaJiYnasGGD3G63HnzwwZM+Z//+/brpppv07W9/W6tWrRr16/7ud79TVlaW3vSmN0mS0tPTA0tXh4eH1dnZqbS0tCD9rE725z//WS0tLfrmN785I98vHGxcmquf/3WPjtV2qaG1jw5NAABeZ3DIrWe210gy90RFCs59keGyc4vVP+jWn/5zSB6voZL8ZF17xUqV5Kec9vNKC1J04Hi7jtV2avPagpkpFgAQNG6PVy/sqtODvq6yj1+2JOLH4HGWCT1nL5+jNYuydaiqXXUtfXp2Z632V7Tpx3/YqZ9ed6Gy0mhyAIKBsAwB/q6y+BinEuNcFlcT3q666irddNNNmj9/vlatWqXHH39cjz76qL71rW8pMdEcz5KamnrS5/iXps6bN09lZWWnfM2uri7ddddd+vnPfx742KZNm/TLX/5SDz/8sA4fPqykpCStXLlyWn8uvb292rVrlySzvb6jo0MvvPCC/vznP+sd73iH3vzmN0/r9wtnyQnRWlqcrj1HW7WtvFHvOL/E6pIAAJgRHq+hB586rMe3VmrE7dWmNQW66pJFiok+8deNJ7dVq6d/RLnp8VqzKNvCaqcX577IYLPZ9P6Ly/SO88zQLD05ZkI7TUrzzRvyx+q6gl0iACCI2rsH9bvHD+jFPfUaGHJLkjavLdA5y+dYXFnwcZYJTdEuh5aXZmp5aaYuXl+oG+58QYeqO/T7fx/UFz+w2urygIhEWIaAhlYzLMvJiA/pZZfh4Morr9Tg4KDuv/9+3XXXXZo3b55uvfVWvf3tbz/jr3nXXXdp1apVWrt2beBjy5cv13XXXacf/OAHSk5O1m233aaYmJjp+CkElJeX68orr5RkPkSIj4/XggUL9K1vfUtXXHHFtH6vSLBmYbb2HG3VzkPNhGUAgFnj7r/t1aMvVgZ+/PfnK/Ta4Rbd+JF1KshOVHffsP74n0OSpHdeUCJHBO394NwXWeJiXIqLmfjFwZK8FElSRV2nvF4jonfaAECk6uwZ0vU/fU7NHQOSpMS4KL1l41x96JJFFlc2MzjLhD6nw65PXb5M1932nLbsrNUH3lymnHSmGQHTzWYYhmF1EQgNDz1zVL9+dL/OX5mn669aO/4nADhFVUO3PvejZxTlcugP37lE0a7QnoUNAMBU7a9o0w0/e0GS9Jn3LFdqYoz+96Hdau8eUkyUQ5dfWKodB5t1qLpDRblJ+skXL5DTEdnjjDB7eDxeve9rj2t4xKOff3mzCrITrS4JADBJN//6Fb28r1HZaXH64gdWa1FRGpcfEJK+eddWvXa4RVdcNF8ffttiq8sBIg5/S0VAfWuvJCk3k5sJwJkqzElUenKMhkc82l/RZnU5AAAE3Z+eMDvGLl5fqLedPU9nLcvVbdddqOWlGRoc9ugP/zmkQ9Udio916X/ev4qgDBHF4bCreE6SJEYxAkA4qmvp1cv7GiVJX//4Bi0pTicoQ8i6eP1cSdKzr9WJ/hdg+vE3VQTUt5hjGOdkJFhcCRC+bDabVpdlSZJeO9RscTUAAARXVUO3dh1ukd0mXXnxiX0VqYkx+r+fOlufvny5lhSn68LV+frhteepND/FumKBIPH/e32sttPSOgAAk/e4b4z0usXZKspNsrga4PTWLclWbLRDze39OlTdYXU5QMQhLEOAv7Msj84yYEpWLzTDsh0HCcsAAJHtP69USZI2LstVdlrcSa857DZdes48ff+z5+pLH1zDeDpErJL8ZEnSUcIyAAgrhmHo5X0NkqQ3b5hrcTXA+GKinFqzMFuStOMAz5yA6UZYBknS4JBbbV2DkqQ5mXSWAVOxcn6m7DappqlHLb4FwQAARBqPx6vnXquTJL1pXaHF1QDWKQl0lnXJ62UkEgCEi+qmHjV3DCjKadfKBZlWlwNMSCAsO9hkcSVA5CEsgySpoc0cwZgY51JiXJTF1QDhLSEuSvMLUiVJuw5z0wcAEJl2H21VZ++QkuKjtMo3ghiYjQqyE+V02DUw5FZzR7/V5QAAJmh7uRk2LCvNUEyU0+JqgInxTzM6Wtuprt4hi6sBIgthGSS9bl8ZXWXAtFhZZt5K23W4xeJKAAAIjm37GyVJG5fmyungrxWYvZwOuwpzzDGjlfVdFlcDAJio/ZVtkqSVC7j0g/CRlhSjwpxEGYZUXtludTlAROFvtZAk1bWY+8rmZLCvDJgOq3yH7V1HWhjHAwCIOIZh6NUD5m3s9YuzLa4GsF7xHHNvWUVdt8WVAAAmwjAMHarqkCQtLEq1uBpgchbPS5cklfsCXwDTg7AMkqT6Vl9YRmcZMC3K5qYqNtqh7r5hVXDDGAAQYWqaetTc3i+X064V89nxAcybkySJzjIACBcNrX3q7huWy2lXSV6y1eUAk7J4Xpok6QCdZcC0IiyDpBNjGPMyCMuA6eB02LWshFGMAIDItM2342N5aYZiotnxAczzPWglLAOA8HDQ11VWmp8il9NhcTXA5Pg7y47Wdmpw2G1xNUDkICyDpBOdZbmZjGEEpsvKBWZY9tqhZosrAQBgem3zjWBctzjH4kqA0DAv1+wsa+4YUO/AiMXVAADG47/cUFqQYm0hwBnISo1VenKMPF5DR6o7rS4HiBiEZVDfwIi6eoclsbMMmE7+sKy8sp2bPgCAiNHTP6wDvv0I6xaxrwyQpIS4KGWlxkqiuwwAwkFVg7ljcm5OksWVAJNns9nYWwYEAWEZVNPUI0lKT45RXIzL4mqAyJGflaCMlFi5PV6VVzBHGgAQGXYcbJbXkIpyk5SVFmd1OUDImDeHUYwAEC6qGs1nYXNzEy2uBDgz/r1l5ewtA6YNYRlU7QvLCrI5IADTyfb/2bvv+Kiq9I/jn5lJ772HEiBAqKGDiIKKqKiou3axY9d1LWv5rbuurg07KjbWAvaGXUARQXrvCS2kkEp6LzP390dIJNISyGSSzPf9evEC7tx757l3kpkz5znnOSYTiQ2lGHeoFKOIiHQOq7dlAzA8QbPKRA7WmCzbV+LgSERE5GhKK2ooKKkCoIv6wqSD6tutPlmWlFqAzWY4OBqRzkHJMmmcWaYGgkjrS4wPA2Cd1i0TEZFOwGq1sTap/jNtmEowijQRF11fymv3viLHBiIiIkfVUIIxLNBTFZakw+oW6Ye7m4WKqjoycksdHY5Ip6BkmZB2YOp5lwgly0Ra2+DeoZjNJtKyS8nOL3d0OCIiIidkW0oB5ZW1+Hq50btrkKPDEWlXesUGAvWdsFXVWq9WRKS9+qMEo9Yrk47LYjHTMyYAgB1pRQ6NRaSzULJMVIZRxI58vdwap8av3pZzzP2tNoOfV6Uxfc4aZn2zRQk2ERFpV1YdVILRYjY5OBqR9iUkwJMgPw9sBuzKKHJ0OCIicgSp2fUzy7pGKFkmHVt8l/qBOjvSCh0ciUjnoGSZk6uoqmV/USWgMowi9jIiIQKA5ZuzjrpfRVUt/3l7BS99sp7F6/cx97fd3PbMQlZuOfpxIiIibcEwDFZurU+WjegX4eBoRNqn3l3VaSUi0t41lGHsqgpL0sHFdwkAYEe62h0irUHJMifXsF5ZkJ87Pl5uDo5GpHMaOygKgC179pNfXHnYfaw2g6dnr2Fdci7ubhYuPLUn/eKCqamz8dT7a9izr7gtQxYRETlERm4ZWfvLcbGYSYwPdXQ4Iu1S7wMjvJOVLBMRaZcMw1AZRuk0GmaW7c0sobrW6uBoRDo+JcucXMN6ZSrBKGI/YUFeJHQPwjDgt3UZh93n3e+2si4pFzdXC/+9eQzXntuP/948hhEJEdRZbTz34VqsVlsbRy4iIvKHVQdmlQ3sGYKXh6uDoxFpn+IbZpalKlkmItIeFZRUUV5Zi9lsIibMx9HhiJyQ0ABPAnzdsdoM9mRokLXIiVKyzMk1rFfWRXWaRexqwrAuAHy/bO8hSa9Fa9OZ+9tuAO6+LJHeXevXOLNYzNx1aSK+Xm6kZZcyf2Vq2wYtIiJykBUHygKPSAh3cCQi7VfPmADMJthfXHXEigIiIuI4ew+UYIwK8cbVxeLgaEROjMlk0qx2kVakZJmTayjDqJllIvZ16tAY/LzdyC2oYMmGfY3b92aVMOOzjQBcfHo8YwdFNznOz9uNSyfGA/Dpzzuo0+wyERFxgOz8cpJSCzGZYNSASEeHI9Juebq7NA5E1LplIiLtT2qWSjBK59JQilHtDpETp2SZk2uo09xFyTIRu3J3tXDeyXEAzPpmK7mFFeQWVPDEu6uoqbUyOD6Uy8/sc9hjJ43qRoCPO/uLq1i6MbMtwxYREQFg0YEywoN6hhLs7+ngaETat94HSjEm7VWnlYhIe5OaXT+zrKsqLEkn0Ss2AIBd6UUOjUOkM1CyzIkVl1Wzv6i+NEj3KDUSROztwvE96RLhS1FZNTc9+TPTnvyZrP3lhAR4cu8VQ7GYTYc9zs3VwtkndQfg+6UpbRmyiIgIhmGwaG19suzUoTEOjkak/esXFwzApl15Do5ERET+LK0xWaZB49I59DyQLMvKL6esosaxwYh0cEqWObHdBxZ+jA711iLtIm3A1cXCP68bSXyXAOqsBlabQa/YAJ6+fSz+Pu5HPXbiyC6YTbB9bwGZeWVtFLGIiAjsyihiX14Zbq4WRqsEo8gxDe4VCsDufcWUlKvTSkSkvbDaDNJy6r9Pd1MZRukkfL3ciAj2Av7o6xWR4+Pi6ADEcXbvKwKgR3SAQ+MQcSYRwd5Mv2NcY+mHbpF+mEyHn1F2sGB/TxJ7h7E2KZdf1qRz1Vl97R2qiIgIAAtWpQEwql+EBliJNEOgnwddI3xJzS5l4848Th4cfeyDRETE7nIKyqmpteLmYiY82NvR4Yi0mh4xAWTnV7Aro4hB8aGODkekw9LMMifWMNqgR4y/gyMRcS5ms4nuUf50j/JvVqKswWnDuwCwcHUaVpthr/BEREQalVbU8MvqdAAmjuzq4GhEOo7E3mEArNqW7eBIRESkQWpW/aDV2AjfIy6DINIR9YoJAGBnRpFD4xDp6JQsc2K7DryB9jjwhioi7dvIfhF4e7qyv7iKTTu1BoaIiNjfT8v3UlNrpXuUHwN7hTg6HJEOY1T/+pKlq7flUGe1OTgaEREBSM0uBaBrhEowSufS80Df7q70IofGIdLRKVnmpMoqasgpqACgR7Rmlol0BG6uFsYl1pfxWbx+n4OjERGRzq62zsZ3v+8BYMopPVs0G1rE2fXpFkSAjzvllbVs2rnf0eGIiAh/zCxTskw6m4aqYTkFFZRWaL1UkeOlZJmTaijBGBHshY+Xm4OjEZHmaljzYsWWLI1SFhERu1q4Jp2CkmqC/Ny15pJIC1nMJsYMrJ9d9uvadAdHIyIicNDMskhfB0ci0rp8vNyIPLAOn2aXiRw/Jcuc1O59RQD0iA5waBwi0jIJ3YMJ8HWnTKOURUTEjqprrXw0PwmAC07tiauLvjaItFTDerPLNmVSXlnr4GhERJxbTa2VzLwyQDPLpHPqGRsA/LHsjoi0nL71OqmdB0YZNEzTFZGOwWI2MXpA/Sjl3zeqFKOIiNjH97/vIb+4itBAT84e093R4Yh0SL1iA+gS4UtNnY1f1qQ5OhwREaeWklmM1Wbg7+NGsL+Ho8MRaXWN65YpWSZy3JQsc0KGYbAtJR+or6UvIh3LSQOjAJViFBER+yirrOWzX3YCcMWZfXBztTg4IpGOyWQycc5J9cnm75akYLUZDo5IRMR5NQwa7xkToHVYpVPqGVs/IUJlGEWOn5JlTigrv5yCkmpcLGbiuwQ6OhwRaaH+ccH4+7hRWlHL5l0qxSgiIq3ri4U7KauspWuEL6cOjXV0OCId2oShsXh7upKVX86S9RmODkdExGk1JMt6xaofTDqnhqV2cgsrKS6rdmwwIh2UkmVOaOvu+lll8V0CcNdIYZEOx2IxM6p/fSnGpZsyHRyNiIh0JvnFlXyzZA8AU89OwGLWyGuRE+Hh7sJF43sCMOenJGrrVBVARMQRdqYXAtCrS4BjAxGxE29PV6JCvAHYnVHs4GhEOiYly5zQlj31ybJ+ccEOjkREjtfYQfWlGJdvzsKqUowiItJKPpqfTE2tlb7dghieEO7ocEQ6hXPHxhHo605OQQXzV+x1dDgiIk6nsLSK9JwyAHqrwpJ0Yj1jAwDYmVHYouNqaq38sCyFdUm5GIbKRovzUrLMCW09kCzrHxfi4EhE5HgN6BGCr5cbJeU1bN6tUowiInLiMnJLWbAqDYCrz0nQeh4ircTD3YVLJ/YG4OOfd1BVXefgiEREnMumnfXfmeOi/PH3cXdwNCL20+tAsqwlM8tq62w8/r+VzPxiE/96azn/+3arnaITaf+ULHMyeYWV5BRUYDab6NNNo2lEOiqLxczoAfWlGJdtynJwNCIi0hnM/nE7NpvBiIQIVSAQaWUTR3YlMtibotJqvl6y29HhiIg4lY078wAY2EuDxqVz6xETAPyxRl9zLFiVyvodeY3//2bxblIyVcZRnJOSZU5m65760TQ9ov3x8nB1cDQiciJOGnhQKUabpsmLiMjx25FWyLJNWZhMMPXsvo4OR6TTcbGYuWJSHwC+WLiLwtIqB0ckIuIc6qw2Vm/LAWBwfKiDoxGxrx7R/phMsL+okqLS6mPuX2e18dkvOwGYNmUAJw2KwmbA3N80sEeck5JlTmZtUi5QX8JNRDq2gb1C8PF0paismm0HyquKiIi0lGEYvPvdNgDGD42la6SfgyMS6ZxOHhxNz9gAKqvr+OCnJEeHIyLiFFZvy6GorJoAX3cG9VKyTDo3Lw9XokJ8ANiVUXTM/Tft2s/+okr8fdyYOKor546NA2DFlixqaq32DFWkXVKyzIlYrTbWbK8fTTOiX4SDoxGRE+ViMTOqf30pxt837nNwNCIi0lGtS85l8+799TNfzuzj6HBEOi2z2cQN5/UHYMHKVPZmlTg4IhGRzs0wDOb+tguACUNjcbGoG1Q6v4Z1y5qTLFuxuX5Zj1H9I3F3tdC3WxAhAZ5UVNWxNinHjlGKtE/6lHAi21IKKKusxdfLjT7dghwdjoi0gpMGqRSjiIgcP5vN4L3v62eVnXNSd8KCvBwckUjn1i8uuLHE0ayvt2AYar+JiNhDWUUNH8xLYltKAe5uFs4Z293RIYm0iYZ1y3YdY90ym81g5dY/kmVQP7Bn9ID6f69PzjvisSKdlYujA5C289v6DABG9Y/AYjY5OBoRaQ2DeoXi7elKYWk121Py6a8SqyIi0gK/rc8gJbMELw8X/npaL0eHI+IUrjkngZVbstmwM4/V23MYkaCqHyIircEwDH5elcY3S/Y0mb175aS+hAVqQJA4h+bOLNuRXkhBSTWe7i4M6vVHX9LAniF8u2QPm3btt2OUIu2TZpY5iZpaK79vzATg1KExDo5GRFqLq4uZkQfKqi7dlOngaEREpCOpqKrl3e+2AnDR+F74+7g7OCIR5xAR7M354+rXBPnfN1ups9ocHJGISOfw0fxkXv50Q2OiLDrUmzsvHtz4niviDOKi/TGZIL+4ioKSqiPu11CCcVjfcFxdLI3b+/cIwWyCfXll5BdX2j1ekfZEyTInsXp7DuWVtYT4e9A/TjNPRDqThlKMv2/MxKrOFhERaaYP5iVRUFJNZIg3U07p4ehwRJzKxafH4+/jxr68Mn5YluLocEREOryk1AI+mp8MwCVnxDPn0Um8/sDpnDGyKyaTqiuJ8/B0dyE23BeA5NTCw+5jGAYrttQny0YfKMHYwMfTlbhofwC27M63Y6Qi7Y+SZU5i0dp0AE4ZEoNZJRhFOpXE+DD8fdwoKq1mbXKuo8MREZEOICWzmO9+r++gv/mCgbi5Wo5xhIi0Ji8PV66Y1BeAj+YlU1pR4+CIREQ6tne+rZ8tf9rwWK6c1Fcz5sWp9e0WBMD2vQWHfTwjt4x9eeW4WMwM7Rt2yOMJccFHPV6ks1KyzAkUl1WzZnsOAOOHxjo4GhFpba4u5sbf7Z9XpTk4GhERae8Mw2DmF5uw2QzGDIxkSJ9DvyCLiP1NHNGFrhG+lFXW8vGB2RAiItJyKZnFbEspwMVi5qqz+jo6HBGHS+hen+zalnL4mWENs8oG9QrBy8P1kMePlWwT6ayULHMC3/6+hzqrQa/YALpG+jk6HBGxg9OHdwFg1dZsikqrHRyNiIi0ZwvXpLN9bwEebhZuOG+Ao8MRcVoWi5nrz+sPwPdLU8jILXVwRCIiHdPPq+sHjY7sF0Gwv6eDoxFxvITu9cmu3RlFVNXUHfL48gPrlY36UwnGBg3Jsr2ZxVRU1dopSpH2R8myTq6sspbvD5TYuWhCLwdHIyL20jXSj16xAVhtBr8eKLsqIiLyZ2WVtbzzXX2ZokvP6E1ooDqURBwpsXcYw/qGY7UZvPPtNkeHIyLS4RiGwZL1+wCYMFzVlEQAwoO8CA30pM5qHLLu2P6iSnamF2Ey1SeYDyfY35OwQE9sBuxMK2qDiEXaByXLOrnPft5BWWUtseG+RxwtICKdwxkjuwLw3dIUrFabg6MREZH26KP5SRSX1RAb7sN543o4OhwRAa47tx8Ws4lV27IbyyKJiEjzpGSWUFhajbubhcT4UEeHI9IumEwmhvUJB2DVtuwmj6080Nbo0zWIQD+PI56jb7cDpRxVilGciJJlndjKLVnM/W0XANdOTsBiNjk4IhGxp/FDY/DzdiO3oIKlmzIdHY6IiLQz6TmljRUHbjx/AK4u+iog0h7Ehvsy5ZT65PXMLzZRXqlyRyIizbU2KQeAgT1DcHWxODgakfZjeEJ9smzN9hwMw2jcvmRjfX/RqP6Hn1XWoG+3QACSlCwTJ6JvyJ1U0t4CnpmzFpsBE0d2ZVjfcEeHJCJ25uHmwuSxcQB8sXBXk8aQiIg4N8MwePvrLVhtBiP7RZDYO8zRIYnIQS47sw9RId4UlFQ1lkoVEZFj27AjD4ChatuINDGwVyie7i7kFVY2lmLMyC1l6558zCYYlxhz1OP7dq+fWZaUWoDVpv4lcQ5KlnVCP69K4+GZS6mptTKkTxi3XDQQk0mzykScwTkndcfdzcKezGLWJuU6OhwREWkn1iblsi45FxeLmevO6+focETkT9xdLdxx8WAA5q1IZdOuPMcGJCLSAdTWWRtnvQzspRKMIgdzd7UwLjEaqG9bAI1VJob1jSAk4OhrF3eN8MXT3UJFVR1p2SX2DVaknVCyrBOprbPx2hcbeemT9dTU2RjWN5wHpg7HxaKXWcRZ+Hm7MWlUNwDe+W4rdVq7TETE6VmtNv737RYAzj05jqgQHwdHJCKH079HCGeN6QbAa59vpLZO7TgRkaPZmV5ETZ0Nfx83YsLUvhH5szNH1a9tv3hDBp/9soMfl+8F4LyT4455rMVipneXIEClGMV5KIvSSWTmlfHga7/z47K9mExw+Zl9+Od1I/F0d3F0aCLSxi45Ix5fLzfSskv5YVmKo8MREREHm7cylfScMny93Lj49HhHhyMiR3H12QkE+LizL6+c75eqHScicjRb99SXlusXF6yKSiKH0Ss2kNOGx2IY8P4P27HaDEYkRDAovnkzMft0q0+WbVOyTJyEkmUdXJ3Vxme/7OCOZ38lObUQb09XHrl+FJdN7I3ZrIaCiDPy9XJj6tl9AfjwpyQKSqocHJGIiDhKeWUtH/yUBMAVZ/bGx9PVwRGJyNF4e7py5Vn17biP5ydRXFbt4IhERNqvbSn1HfgJB9ZWEpFD3Xj+AMYMjMRkgiF9wrjzksHNPrZvd80sE+eiaUcdVHllLcs3Z/Llol2k55QBMLhXKLf9dRARwd4Ojk5EHO2MkV2Zt2IvuzKKeeHDdTw6bbQS6CIiTujTn3dQUl5DbLgPk0Z3c3Q4ItIMp4/owg/LUtizr5hPf97BjVMGODokEZF2xzAMdqYXAtC7a6CDoxFpv7w9XXnw6hFU1dTh4dayVEDvLoGYTJCdX0FhSRWBfh52ilKkfVCyrIPYmV7IorUZ7M0qISO3lIKSP0YY+nq5csP5/Rk/NFbTzkUEAIvZxN8vH8rdL/7Ghp15fLloF3+Z0MvRYYmISBvKzi/nmyV7ALju3P5YtI6tSIdgMZu45pwEHnlzOfNWpnLJGb3x83ZzdFgiIu1KXmElxWU1WMwm4qL8HR2OSLvX0kQZ1Cfaukb4sTerhO17CxgzMMoOkYm0H/rG3M7ZbAZvzt3M319czDdL9rBp1/7GRFlYkBfXnJPAWw+dwYRhXZQoE5EmYsN9mXZgJPLsH7c31nMXEZHOzzAMXv1sI3VWG4PjQxnaJ8zRIYlICwyODyUu2p/qGivf/77H0eGIiLQ7O9OLAOgW5Yebq8WxwYh0Yg2lGLerFKM4Ac0sa+dm/7idbw+MCB6XGE1ifBix4T5Eh/lqzQkROaYzRnRh8679LFqXwTOzV/Pi3adq2ryIiBP4afleNuzMw83Vwi0XDtSgKpEOxmQy8ZfxvXhmzhq+/X0PF5zaEw93fX0XEWmwI62+BGOvWJVgFLGnvt2C+HHZXranKFkmnZ9mlrVjW3bv5/OFOwG4+7JE7rtyGKeP6ELvrkFKlIlIs5hMJm77yyC6RPhSUFLN9DlrsVptjg5LRETsKD2nlP99uxWAq8/pS1Soj4MjEpHjMWZgJBHBXpRW1PLr2nRHhyMi0q40zCzrFRvg0DhEOrt+ccFA/RJBxWXVx9hbpGNTsqydstkMXvtiEwBnjurKhGFdHByRiHRUHu4uPHj1cDzdLWzevZ9Pf97h6JBERMROsvPL+ddby6mqsTKwZwiTT4pzdEgicpwsFjPnnNQdgHkrUx0cjYhI+2GzGezKKAIgvotmlonYU1igFz1i/LEZsGJLtqPDEbErJcvaqZVbs0nPKcXb05VrzklwdDgi0sHFhPly618GA/DpLzvZl1fm2IBERKTVrUvO5b6Xl5BXWEl0qDf3XzUMs1nlF0U6svFDY3GxmNmdUcyuA7MoRESc3b68Miqr63B3sxAbphn0IvY2ekAkAL9v3OfgSETsS8mydmrub7sAOHtMN3y83BwcjYh0BqckRjO0Txh1Vhuvf7kJwzAcHZKIiLSCquo63v56C/96czlFZdXERfnz5K1j8fdxd3RoInKC/H3cGXOgg0qzy0RE6jWsV9YzJgCLRV2bIvZ2SmIMJhNs2JFH5n4NvpbOS58o7dC+vDK2pRRgNpsay26IiJwok8nETRcMxNXFzIYdeSzbnOXokERE5ASt2Z7DbdMX8vXi3UD9QKtn7jyZQD8PB0cmIq1l4qiuAPy2LoOq6joHRyMi4nhar0ykbUUEezO0TzgAX/+228HRiNiPkmXt0C+r0wAY0juMYH9PB0cjIp1JZIg3F47vCcAHPyVhs2l2mYhIR1RYWsX0OWt49O0V5BZWEhroySPXj+SWiwbh7mpxdHgi0ooG9AghMtibyuo6DXYSEQF2ptfPLFOyTKTtXHBqDwB+Wr6X5NQCB0cjYh9KlrVDyzZlAjBhaKyDIxGRzmjKKT3x9nAhPaeUpQfeb0REpGMwDIOFa9K49emFLF6/D7MJppzSg1fvm8DwhAhHhycidmA2m5gwvP67YcPAShERZ1VbZ2PPvhIA4rsEOjgaEecxsGco4xKjsRnwr7dW8PvGfRqALZ2Oi6MDkKay9pezL68ci9nEkD5hjg5HRDohH09Xzh/Xgw/nJ/PR/GROGhiF2WxydFgiInIMeYWVvPr5BtYm5QIQF+3PHX8dTE+Nqhbp9MYPjeWDn5LYvHs/uYUVhAV6OTokERGH2JtVTJ3Vhq+XG+FBei8UaUu3XDSIvMJKtu8t4On31xDk58HJg6M5bXgs3aP8HR2eyAnTzLJ2Zm1SDgB9uwfh7enq4GhEpLM6d1yPxtllq7ZlOzocERE5CsMwWLAyldumL2RtUi6uLmamnt2X5+8ap0SZiJMID/JiQI8QDAN+XZvu6HBERBwmOfVACcYuAZhMGvQp0pZ8PF15/OYxXHJGPN4eLhSUVPH14t3c+dwiXvp4PTW1VkeHKHJClCxrZxpGCg87sGiiiIg9+Hi6cuaobgD8uHyvQ2MREZEjq6yu4/kP1/HypxuorK6jT9dAXvr7qfz1tHgsFjXlRZzJaQdKMS5cnY5hqOyRiDinbSn1ayUldA9ycCQizsnN1cKVk/oy+9FJ/N+1IzhpYBQmE/y8Oo1H315BbZ3N0SGKHDd9w25HqmutbNqZB8DQvkqWiYh9TRrdDYD1yblk55c7NhgRETlESXkND81cyqJ1GZjNJqae3Zenbj+Z2HBfR4cmIg4wZmAUHm4WMveXk7S30NHhiIi0OcMw2LonH4CE7sEOjkbEubm6WBjZP5IHrh7O4zePwdPdhU279vP6l5s0qEc6LCXL2pEtu/dTU2cjxN+DrhHqBBER+4oM8SYxPhTDgHkrUh0djoiIHKSotJqHXvudXelF+Hm78cQtJ9XPJtMakyJOy9PdhTEDowD4ZU2ag6MREWl7uYWVFJRUYTGb6KVS1CLtxsCeodx/1TDMJpi/MpUflu11dEgix0XJsnYgOzubYcOG8dV3C4H6WWVHqrtcV1fHm2++ycSJExk8eDDnn38+P/zwQ1uGKyIdSF5eHv/3f//H+PHjSUxM5MILL2zynnHWmG4ALFiV2mSqfGpqKnfddRdjx45l6NChXHbZZSxfvrytwxcR6dB+//13LrroIgYNGsSECROYNWtWs0ZZ1tZZ+e87K9mbWcS+Za9Qk/w+/eKOPHr6iSeeoHfv3q0Zuoi0UxOG1ZdiXLwujeeef4FTTjmFQYMGcfnll7Nx48YWnWvLli3069ePL7/8snHbjBkz6N279xH/rFq1qlWvR0QE/ugXW7ly5VH325aSj81ah5GzlCnnTWbw4MGceeaZvPLKK9TU1LRRtCLyZ7Nnz+b+2y7jmsn9AHjv+23kF1cedt99+/Zx1113MXr0aEaOHMmtt95KWpoGAUn74OLoAJxdVlYW119/PaWlpexIKwRXL4YeZb2yGTNm8Oabb3LbbbcxdOhQFixYwN13343FYuHMM89sw8hFpL2rqanhhhtuoLS0lDvvvJOwsDDmzZvH3XffTU1NDVOmTGF4QgRBfh4UlFSxYnMWJydGU1hYyJVXXklAQAAPPfQQPj4+fPbZZ1x33XW89957jBgxwtGXJiLS7m3YsIGbb76Zs846i7vuuou1a9cyffp0rFYr06ZNO+JxhmEw84tNJKUWUpa6mPKCNDx6Rhxx/9WrV/P+++/b4xJEpB0a0COE0EBPti75mO1Za7n/vnuJjo7mnXfe4ZprrmHu3Ll07dr1mOepqanhgQceoK6ursn2v/71r5x88slNttXW1nL33XcTGhrKwIEDW/V6REQO7hc7lm0pBeRt/ZqKrA3ceeftDBgwgM2bN/Pqq6+SmZnJE0880QYRi8jBvv/+e5566inCw8M5f1wPlm3KJCm1kP99s5X7rhrWZN+qqiquu+466urq+Oc//4m7uzsvv/wyV111Fd9++y1+fn4OugqRekqWOYjNZmPu3Lk8/fTTjdvyi6vwCzcxqFfIEY/74osvmDx5MrfffjsAo0ePZuvWrcyZM0fJMhFpYtGiRSQlJfHZZ581dmycdNJJZGZm8vbbbzNlyhRcLGYmjuzKxwuS+WF5CicnRjN37lwKCwv5/PPPCQ8Pbzzu/PPPZ9asWUqWiYg0w4wZM+jbty/Tp08HYNy4cdTV1fH6668zdepUPDw8DnvconUZLFiVRk1JJvk7FxIaGnrE5ygvL+fBBx8kPDyc7Oxsu1yHiLQvZrOJoXEeLJ2znCHjr+Cqq64CYOzYsZx55pm89dZbPP7448c8z4svvnjYjumIiAgiIpom6J988knKy8v5+OOPj/jeJSLSUofrFzuWjdtTKU5bxcVX3dQ4+Gj06NEAPPfcc9x7770EBQXZJV4RaSo/P5+XXnqJTz75hICAAKC+nXLLRYO4+4VFLN6wj4mjujKo1x/fZ9asWcPevXt59913G393u3fvzllnncUvv/zCBRdc4IhLEWmkMowOkpyczL/+9S+mTJnCM88807g9oXswXh6uRzyupqYGHx+fJtsCAgIoKiqyV6gi0kH5+PhwySWXMGDAgCbb4+LimkxxnziyK2YTbNmdT3pOKeHh4VxzzTWNiTIAi8VC165dNTVeRKQZampqWLlyJWeccUaT7WeeeSbl5eWsXbv2sMcVlFTx5lebMWx1VO6ey9VXT6V79+5HfJ5nnnmGkJAQLrzwwlaNX0TaN29rJhg2iszdSM0uAcDNzY1TTz2V33777ZjHr1u3jjlz5vDII48cc9/k5GRmz57N7bffTkxMzAnHLiLS4Ej9YkdSUl5DWmY+/l1H8dcpZzV5LC4uDoD09HS7xCoih3r99df5/fffmTFjBuPHj2/cHhftz9lj6r/DzPpmC1bbH2Xoq6urAfD29m7c1pBoU9+2tAdKljlIZGQkCxYs4MEHH2wyOu9oJRgBpk6dyty5c1m8eDFlZWV88803LFmyhPPPP9/eIYtIBzNmzBj+85//NFkDsba2lt9++42ePXs2bgsN9GR4Qv0I4h+X7+Xss8/m3nvvbXKu4uJiVq9eTa9evdomeBGRDiw9PZ3a2lq6devWZHtDabSUlJRDjjEMg9c+30hZZS227CV4u1u48847j/gcS5cu5euvv+bJJ5/EbFaTXsSZ5GWn4+rmgYuHL98u2dO4vWvXruTm5lJeXn7EYysrK3nwwQe56aabmrXW4TPPPENMTAxXX311q8QuItLgSP1iR7IuKQdXryBGnDGVgf37NHnsl19+wdXV9ZC2l4jYz6WXXsq8efOYOHHiIY9ddmYfvD1cSMks4dc1fySxx44dS48ePZg+fTrp6enk5eXx2GOP4eXlxemnn96W4Ysclr5ZO0hAQEBjeYuaOmvj9mF9w4563DXXXMPQoUO58cYbGTp0KPfddx9TpkzhhhtusGu8ItI5TJ8+nb1793LzzTc32d4w6ueX1WlUVTddu8Jms/HPf/6TsrIyvdeIiDRDQ2mzP1cDaBhBWVZWdsgxa5NyWbk1m9qSDNI2/8LTTz+Fm5vbEc//8MMPc+eddx515pmIdE6lpaX4+voC8OvaDErKa4Cjv8c0eO655/Dy8uKmm2465vMkJSXx+++/c+ONN+LiohUcRKR1Hdwv1hwrt9aXnB7Rr+kxCxYs4KuvvuLSSy/F39+/VWMUkSPr0aMHrq6Hr47m5+3GxafXD8qZ/eN2qmrq+5nc3d3573//y44dOzj99NMZO3YsP//8M6+88gqxsbFtFrvIkShZ1g7s2VcMQICvO7Hhvkfcr6amhiuuuIJt27bx6KOPMnv2bP7+97/zww8/NKsuvYg4L8MweOaZZ3jvvfe4/vrrDxn5Mzg+lMhgbyqq6vht/b7G7bW1tdx3333MmzePhx9+WIu6i4g0g81mO+rjf54JZrXa+N+3W7BZaylJ+pJrrrn6qO+3TzzxBBEREVxzzTWtEa6IdDCGYeDqYiYu2p+aWis/LGs6W/VIs01XrlzJJ598wpNPPtms5NcHH3xAcHCwqpiIiMNV11pZm5QLwMiDkmXz58/n73//e+NgchFpPyaP7U5YkBcFJVV8/dtuAFatWsXUqVPp06cPb7zxBm+99Rbjxo3j9ttvZ82aNQ6OWETJsnZhR1oRAL27BDYpl/Zn8+bNIykpiWeffZZLL72UESNGcNNNN3Hfffcxe/ZsduzY0UYRi0hHUlNTwz333MOsWbO4/vrruf/++w/Zx2w2MWl0fXmwH5enYBgGJSUlXH/99fzwww/885//5Iorrmjr0EVEOqSGGR9/LoXWMNvjzzPO5q1MJT2njNI9P+Pj5cqtt95KXV0ddXV1GIaBYRiN//7111/5/vvveeyxx7DZbNTV1TUm5w7+t4h0Xj4+PpSXl3PR+Pqy2l8t2kVJeU3je0zDe9DBysvLefDBB7nxxhvp2bNnk/eLhveSg1mtVhYsWMCkSZOOOMtVRKStLN+USWV1HWGBnvSKDQTg3Xff5a677mLIkCG88cYbuLu7OzhKETmYm6uFq8/uC8DnC3eSnV/O66+/Tnh4OG+99Rannnoq48aNY8aMGfTq1YsnnnjCwRGLgGopOJhhGCSnFgDQu2vgUffNzMwEYMiQIU22Dx8+HIBdu3YRHx9vhyhFpKMqLS1l2rRpbNiwgYceeuio602cNrwLc35KYndGMcvX7eCx//sbGRkZPP/885x11llHPE5ERJrq0qULFouF1NTUJtvT0tKA+pIlDcora/ngpyQAavZvJSc/l8TExEPO2a9fP5588klWrVpFdXU1kydPPuw+F1xwAU899VRrXo6ItDNxcXGUlZWREOtJXJQ/ezKL+eyXHaSnphIdHX3YtX+2bNnCvn37ePXVV3n11VebPPbwww/z8MMPk5yc3Lht48aNFBYWqg0oIu3CTyvq21RnjOyKyQSPP/44s2fPZvLkyTz55JNK6ou0UycPjuaHZXvZuiefp2evYd++ffTv37/J76zZbGbo0KF88MEHDoxUpJ6SZQ6WkVtGYUk1AHHRR6+tHBcXB8CaNWsYO3Zs4/Z169YBEBMTY6coRaQjqqur4+abb2bz5s288MILTJo06aj7+/u4c9KgKH5ZsYu/3XET1upS3nnnHYYNG9ZGEYuIdA7u7u4MGzaMBQsWcP311zdWDpg3bx6+vr5NSix+9ssOSspriAnz4elZb2Gtq21yrn/9618APProo8TExDBixIhDZvp++umnfPrpp3z++ecEBh598JWIdHxjxowBYP78eUw95zT+/dYKvvltJwWrf+XUU8Yd9hjfkC4MPfd+8gorG7fVVZeSufpdgnqdTo++w1iwMpUJw2KxWMxs3LgRFxcXleAWEYdbm5TD1j35uFhMnD68C88//zyzZ8/m2muv5R//+MdRKzSJiGOZTCb+fvkQ7npuEbvSizB7hLBp0yZqamoaE2aGYbB+/XqtWSbtgpJlDrZ8c1bjv91cLU0eKysrY9euXXTp0oWgoCAmTJjAoEGDuO+++7jjjjuIi4tj06ZNzJw5kwkTJuiLjIg08cEHH7BmzRouueQSIiIi2LBhQ5PHBw8eDNTPdCgoKGDw4MGcd3Icn77/GsX5WVxz/U24uLg0Oc7NzY2EhIS2uwgRkQ7qlltu4dprr+Wuu+7ioosuYv369cyaNYt77rkHT09PAHan5fDR3F8xewRy3bkjSeh76CL33t7eAAwYMACAwMDAQwZILVq0qMk+ItK5RUdHc8EFF/Dkk09y991VhJgrWb/0e2pLirj22usa92to4+XXBvHaF5uoMUKI6uLO+eN60qtLAHtS0rh/9bt4+4VQbAvi5U83MHfxbqZNGcCOHTuIiYlRWTMRcaide7N58rWvqbP5MGXiIPKy9vLWW28xYMAAJk2axMaNG5vs37Nnz0PKXYuI4zS0Re6+bAiP/W8ldSGjydr5OldcdQ03T7seFxcXvvjiCzZs2MDLL7/s6HBFlCxztGWbM4/42NatW5k6dSpPPvkkF154IRaLhf/973+88MILvPbaaxQXFxMbG8stt9yiBd5F5BDz588H4JNPPuGTTz455PGGUjuvvfYaX331FcnJyfSKDaRm/zYA3p31Bu/OeqPJMdHR0SxcuNDOkYuIdHyjR49mxowZvPzyy9x2222Eh4dz//33c911f3Rkv/zeT+xdMoPhE69jWN9wB0YrIh3Nf/7zH/z8/Hj77bcpLy/H4hNF5Igb+HplIXd07YqLxcyMGa/wzTdfEz/5GQCG9AnjnsuH4uddP5I70L0KgOvP6497eD8+X7iDtOxS/u/1ZdTtSsHP7+iVT0REWpvNZrBsUybbUgrYmV7I+nVrSF36On3GXsUlZ1zMrDdfwzAMNm/ezCWXXHLI8e+//z4jR450QOQicjgH9zfdefFgXv3cRPSom9iVPI877rwbVzdX4uN78/777zNixAhHhyuCyTAMw9FBOKvs/HJufOJnzCZ4/9+T8PfRqD0RcbwdaYXc89JizGYTM/8xgagQjcwTEWltW3bv58HXlmI2wYt/P5XuUeqUFpHjt3JLFk+8txqbzSA23IdesYFs2pnH/uIqTCa4/Mw+XHxaPGbzkcuVlVbUMPvH7fy4bC8AJw2M4r4rh2KxmNvoKkTEmWXnl/P4/1aSml3aZPvAniHcfdkQQgI8HRSZiLSWtOwSPvl5Bys2Z1FTZ2vcftLAKK6ZnEBEsLcDoxNRssyhvlq0i/99u5WBPUP47y0nOTocEZFGj769gjXbcxjaJ4x/3TBKdeBFRFqR1Wbw9xd/Y8++YiaN7sZtfxnk6JBEpBNYsSWLlz5eT1nlH2sfhgR4ctclgxkcH9bs8/y+cR/PfbCOOquNM0d15fa/DrZDtCIif0jJLOZfby6nsLQaXy9XxiXGEN8lgPgugcSE+To6PBFpZRVVtazams2yzVms3JKFzQAXi5nzTo7j4tPj8fZ0dXSI4qSULHOg+15eTFJqITdfMIBzxsY5OhwRkUbpOaXc+dwi6qw27rl8CKcO1UKrIiKtZd6KVF75bAPeHi688eDpqi4gIq2mrKKGJRszKS2vISrUm2F9wvFwb/nqCyu3ZPHEu6uwGXDflUMZlxhz7INERI5DbmEFf3v+N0oraugW6ce/bxxFsL9mkYk4i71ZJcz6ZgsbduQBEOzvwd2XDWFQr1AHRybOSPUUHCQzr4yk1EJMJhg1INLR4YiINBEb7sulE+MBeHPuFvIKKx0ckYiI/VhtBvvyykjPKaWm1mrX5yqvrGXOj9sBuHRibyXKRKRV+Xi5cdboblx8ejxjB0UfV6IMYGT/SP56en1b8NXPN5KdX96aYYqIAFBbZ+Xp91dTWlFDXLQ/T942VokyESfTLdKP/0wbzSPXjyQyxJv84ir+7/VlfDQvCc3xkbZ2fC1nJ1RbZyM7vxw3VwuhAZ5HrfXeHD8u3wvA0D7hagiISLt00fheLNuYxZ7MYv711nKevn0svl5ujg5LRKRV/bwqjdk/bqOgpBoAs9lEl3Bf4qL96Rrhi4+XG14eLoQHeREXHYDlBNuA73y3laKyaqJDvTnnJFUWEJH267IzerNp53627y1g5heb+PeNKs0tIq3rrblb2JFWhI+nKw9dMwIflV4TcUomk4nhCREM6BHC299sYd6KVD6cn0xeUSW3/mUQLlo/VdqIyjAeQ3FZNR/8lMQva9IbRxp7e7py8uBo/npaL8ICvVp8zvLKWq5/fD7lVXU8cv1IhidEtHbYIiKtIrewgvtnLCG/uIreXQL5142jlDATkU7jkwXJzPkpCQA3VwsuFhMVVXVH3D800JOpZ/U97tK0a5Ny+PdbKwB44paTGNAz5LjOIyLSVjL3l3HbMwupsxr864ZRDOsb7uiQRKST+H5pCq9/uQmTCR65Xu8vIvKHH5fv5fUvNmIz4KRBUdx3xVAsSphJG1Cy7Cj27Cvm32/VLzAK4OluobbOoM5qA+oXHpw8tjuXnNG7RaNfPl6QzAc/JREb7ssr944/4VlqIiL2lJpVwj9e/Z3yylqiQ334942jiAj2dnRYIiInZNW2bB6btRKAS8/ozcWn98LFYia/uIrdGUXs2VfMvrxyKqprKa+sJTWrhPIDibS/TOjF1ecktOj5yipruX36QvKLqzj35DimTRnQ6tckImIP73y7lS8X7SI61IdX7huv0d0icsLWbM/hsf+txGYzuPqcBP4yoZejQxKRdmbFliyefn81dVaDkwdHc8/lQ5QwE7tTsuwIdqUX8c83llFWWUtsuA+3XDSI/nHB2GwGW/bk88mCHWzevR8AP283rjyrLxNHdj1maZ7cwgpue2YhVTVWLZQsIh1GalYJ/35rOfuLqwjwdeeR60fSKzbQ0WGJiByXiqpabn7qFwpLq5uduKqptfLZLzv5eEEyADddMIDJY5tfRvGFj9axcE06kSHevPz3U497HSERkbZWXlnLTU/9THFZDTee35/zxvVwdEgi0kHZbAYLVqXx+pebqLPaGD80hrsvG6ISryJyWKu2ZvPke6uosxqMGxzN35UwEztTsuwwMveXcc+LiymrrKV310AevXE03n+aOWYYBuuSc5n1zRbSc8qA+gUJb5zSn4E9Qw973to6G4+8uYwtu/NJ6B7Ek7eO1awyEekw8osrefTtFaRkluDmauHeK4YwekCUo8MSEWmxd7/byhe/7iIyxJtX7h2Pm6ul2cd+sXAn736/DVcXMy/efQpdIvyOecwvq9N48eP1mEzw1G1jSegefCLhi4i0uXkr9vLKZxvx9nTljQdOw9/H3dEhiUg7Z7UZZOaVkVNQQV5hBVn5FazZnkN6TikAJw2M4p4rhuLqoo5vETmyFVuyeOq91VhtBqckxnD35UNOeB1pkSNRsuxPKqpqufflJaTnlBLfJYDHbhqDl8eRSyzWWW38uGwvH85LoqyyFoCE7kFMHhvH0D5hjcfmF1fy8qcbWJeUi6e7C8/dNY7YcN82uSYRkdZSUVXL07PXsC4pF5MJrjkngQtO7dmskYBWm8HvG/axfkcuFVV1RIV4M3ZwND1jAuwfuIjIASXlNVz3+Hyqa6z88/qRjGjh2rGGYfDo2ytYm5RLjxh/pt8x7qidPCmZxdz70mJq6mxcNrE3l5/Z50QvQUSkzVltBne/sIiUzBLOHtONWy4a5OiQRKSdslptfL8sha9+3cX+4qpDHvd0d+HSM+KZckpPDSAXkWZZvjmTp99fg9VmcNKgKO68ePBR++tFjpeSZQex2QyeeHcVK7dmE+TnwQt3n0KQn0ezji0pr+GjeUn8tGIvddb6W2oxm+gW5UdFVR3Z+eUYRv3i8Q9fO4IhvcPseSkiInZjtdp46+stfL80BYCJI7tyy0UDj7p+xbaUfN6cu5ndGcWHPHbSoChuvWgQft5udotZRKTBBz8l8fGCZOKi/Xnx7lOOq+xPQUkVt09fSGlFLZecEc+Vk/oedr/yylrufvE3svaXM6RPGP+6fpQ6hUSkw9q8az8PzVyK2QQv3TOebpHHnlkrIs6lqrqOJ99bzbrkXADc3SxEBnsTFuhFeLAXcVH+jBoQiY+nOrlFpGWWbcrkmdn1CbOoEG/uvXKolgeRVqdk2UE+nJfER/OTcbGYeeq2k+jdNajF58gvruSHZXv5fcM+MveXN3msX1wwN57fnx6aRSEincC3S/bw9tebsRkwsGcId12aSFigV5N98osrefe7bSxalwGAt4cLk0Z3I9jfk+17C1i6KRObzSA8yIt/Xj+Srs0oZ9ZSxWXVbN2TT0FJFd6ervSLCz4kThFxDhVVtVz3+ALKK2t5YOpwThp0/KVkl2zYxzOz12A2m5h+x8nEd2n6Rc1qtfH4O6tYsz2H0EBPXrz7VA0KEJEO78n3VrFsUxYDe4bw+M1jtM6QiDTx0sfr+Xl1Gu5uFq4/tx+nj+iCq0vzy12LiBzN1j35PDtnDfuLqzCb4PxTenL5mb3xcNN60NI6lCw7YNmmTJ58bzUAd12SyOkjupzwObPzy0nJLMbDzYXuUf4E+Kquu4h0Lqu3ZTN9zhoqq614uFn462nxjOgXQVVNHSs2Z/H90hSqaqyYTHDGiK5cdVbfJu+FuzOKeOr91WTnV+DpbuH+q4YzrG/4CcVksxmkZpewelsOq7dlk5xWyMGfdCYTnJIYw41TBqjjWsTJfPnrLt75bivRoT68ev+EE651P332GhZv2EdMmA/P/+0UPN3rv6QZhsHMLzbx4/K9uLmYefK2sYck00REOqLs/HJufWYhtXU2bv3LIM4a3c3RIYlIO9HQr2YyweM3j2Fgz1BHhyQinVBJeQ1vfLmJxRv2ARAe5MVtfxlEoqq4SStQsgzYnlLA/72+lJo6G+eeHMe0KQMcHZKISIeRnlPKK59tYFtKwWEf79M1kJsuGEjP2IDDPl5SXsNT761m8+79mE1ww/kDOPfkuBbFkFdYybrkHDbsyGPz7v0Ul9U0ebxbpB9Rod7kF1eRnFoIQFigJ0/cOpbwIM0yE3EGNbVWbvjvAgpLq7nrksGcPqLrCZ+ztKKG26cvpKCkmiG9w/jH1GG4uVp497ttfL14NyYTPHj1cEYPOP4ZbCIi7c3c33Yx65utuLtZePnvpxIV6uPokETEwepLVP9KaUUNf5nQi6vPSXB0SCLSya3els1rX2xif1ElABOGxXLTBQO0lpmcEKdPlqVll/DAq79TWlHL8IRwHr5mBJajrLsjIiKHstkMFq3LYN6KvaTnlOJiMRPfJZDTR3RhZL+IY5boqa2zMfOLjSxYlQbAGSO6cP15/fE+Si37zP1l/LZuHyu2ZLFnX9O10NzdLAzoEcKIfhEM7xtOSIBn42M70wuZPnstWfnlSpiJOJEfl6Xw2hebCAnw5M0HT8fVpXXae0mpBTw8cxk1tVa8PV1xdTFTVFoNwE0XDGDy2JYl/0VE2jubzeCfbyxj0679xEX789RtYxtn1nY2JeU1rNySRXJaIf3jgjl1aKyjQxJpdwzD4N9vr2BdUi5x0f48e+e4VmtniYgcTUVVLXN+SuK73/dgGBAb7sND14wgJszX0aFJB+XUybLUrBL+7/VlFJVVE98lgP/efBIenbCRn5+f7+gQRMTOgoODHR3CCTMMgy9/3cV7P2zDMCDIz4MrJvVh7KAovDxcMQyDotJqVmzN5tc16Wzf+8dMNpMJ+nQNYnB8KIN6hRLfJfCoX9Dyiyt56LWlZO4vJzrUm+l3jsPXSyUZRTorq9XGtKd+IbeggmlTWj579Vi2pxTw7AdryC2sH9UY4OPOtAsGcPLg6FZ9nhOh9qBIx9Re23h5hZX87YVFlJTXMLBnCA9fO6JTjeTelV7E5wt3smJLFlZbfZdJZLA3bz50uoMjE2l/vv99D69/tRk3FzMv3H0KXeywDvWJUjtI5Pi117bIwbbuyeeZ2WsoKKnCy8OFB6YOV1lGOS5Omyzbsns/T763mpLyGuKi/XnspjGddu2a6Oj201EjIvaxb98+R4fQajbtyuOVzzaStb+8cZu3hwsGUFFV17jNbILBvcM4eVAUwxMi8Pdp2bqQ+cWV3DdjCXmFlQzoEcKj00ZrBKRIJzVvxV5e+Wwj/j5uvP3wGXZZANpqtZGUWojVZiM+NrDdDcBSe1CkY2rPbbzk1AL++cYyKqutRAR7cefFiQzoGeLosE5IXmEls77ZwtJNmY3bukf5MTwhglOHxBAbrpHq0vnU1tlYl5RDUmohNXVWuoT7Map/875fpeeU8rfnF1FTZ7PLgKTWonaQyPFrz22RgxWWVPHke6vZvrcAs9nEzRcM4Kwx3R0dlnQwTpcss9oMvv5tF+/9sB2bzaBnbACPTRuNTyeeUaBGgUjn11EaL81VXWvl+99TmL8ylX15ZY3bTab69cfGD43llCExBPl5nNDz7M0q4f4ZS6isruOMEV244+LBxywZ6QgFJVUUl1Xj7+N+wtcs4myqquuY9uTPFJZWc8P5/Tl/XA9Hh+QQag+KdEztvY23M72QJ95d3bheyMCeIZw1phvD+obbZWCCvdTWWZn7224++XkH1TVWzCY4ZUgMF43vRdfI9jdLRqS1rNySxetfbmJ/cVWT7a4uZi4c35O/nhaPu6vlsMdW1dTxjxm/syezmMT4UP5942jM5vb3XQrUDhI5Ee29LXKw2jorL3+6gUVrMwA4b1wc153bH0s7fW+S9sepkmXbUvJ5c+5mdmfUr21z6pAYbvvroA7ViD8eahSIdH4dqfHSUsVl1ZRW1GCzGUQEe+N2hC9rx2vN9hwem7UCmwFXn5PAXyb0atXzH6/aOhvzV6aycE0aO9KKGrdHh3ozsl8k4xKjiYv2b5fJPZH25KP5yXw4L4mIYC9eu/80p51BqvagSMfUEdp4FVW1vPPdNuat2EtD74Kbq4WhfcIYMyCS4QkRR12H1tE27Mjl9S83sS+vvqpBQvcgbr5wIN2j/B0cmYj9FJZW8cZXm1m6sX4WZZCfOyP6ReLhZmHTrv2Na0KHB3lx84UDGdY3vMnxVpvB9DlrWLoxEz9vN16+51SC/T0PeZ72Qu0gkePXEdoiBzMMg09/3sGcn5IAGNInjPuuGNqpJ8pI6+nUybKyylpS9hWze18RK7Zks3VPfY1ib09Xrp3cj4kjuzhFJ6MaBSKdX0drvLQ33/2+hze+2gzAA1cP56SBUQ6NJyWzmOlz1pKeUwrUz6jz93GnpKwa20Gf2lEh3vTuGsiEYbEMjlc9bjkxNpvRbkcDH6/s/HLuePZXqmqs3H/lME5OdN42kdqDIh1TR2rj5RZU8NOKvfy2fh+5BRWN210sJgb1CuXkwdGMHhDZbtY2KyipYtY3W1i8vv4eB/q6c+25/Th1SIxT9BOIc6qptTJvRSofzkuirLIWs9nEhaf25NKJvRtnkBmGwbLNWbw1dzP5B2acDekTxqRRXUnoHkxOQQUf/JTEuuRcXCwm/jNtTLsvwap2kMjx60htkYMt2bCPFz9eT01tfbnoh64ZoYEwckydJllWVlnLjrRCdmcUsXtfMXsyisnKL2+yj4vFxIRhXbjyrD4E+jpPGSstZCrS+XWEBVfbuze+3MR3S1NwczHzj6nDGdEvos1jMAyDH5amMOvbrdTW2Qjwceevp/Xi5MHRBPp5UFFVy7rkXH7fmMmqrdnU1tkACPBxZ/ajk9o8Xuk8vl+awltzN+Pl4UJMmC/DE8I5eXA0EcHejg7tuNXWWXnotaUkpRbSLy6YJ289yak7P9UeFOmYOmIbzzAM9uwrZvnmLJZtziQ954+S2m6uFkb2i+DUoTEM6R2Gi6VtZ/tW1dSxM62IxRv28cvqNGrrbJhNcPZJ3blyUt92PQNOOr6s/eX8ujYdABeLGW9PV0IDPOkW5UdYoFerP19tnY3M/WWk55SSnl1Kak4p21PyKSipBqBHjD93/HUwPWICDnt8RVUtH81P5psle7DZDu06dHUxc9+VQxk9wLEDDZtD7SCR49cR2yIN9uwr5r/vriK3oAJ3NwvXnpPAmaO7Hbb9UVVdx/a9BWTkllFUVo3FbMLHy5XYMF96xATg562Zac6gwybLSitq2LYnn82789m8ez8pmcUc7krCgrzoEe1Pz5gAJgyLJSSg/U4LFxERx7FabTzx7mpWbcsG4JyTuvPX03q1WTmR8spaZny2obEUyvCEcO66JPGIC2uXVdaStLeA3RlFxEX7Mzyh7ZN70nn8uHwvM7/Y2KQtZTLB6AGRXHhqT3p3DXJccMehptbKsx+sZfnmLLw8XHjp76d26MSfiEhHlp5TytJNmSxam9FkLVpfLzdG9Y8gMT6Mgb1CjtjmORFllbVs25PP1j35bE3JZ3dGEXXWPz7s+nYLYtqUAfSMDWj15xb5s5c/Wc+CVWmHfSws0JMxA6M4fXiXE1onLyO3lN/W7WN9ci67MoqwHibJFeLvwcWnxzNxZFcszUhY78srY8HKVH5bv4/9RZV4ulsY0iecK87sQ2y473HHKiLSFkrKa3h2zhrW78gDICTAk0mjutI9yp+yyhoycsvYsjufHWmFh33PbBAW5MWgniEk9g4jMT5UZR07qXafLCspr2HhmnSKSqsoq6wlr7CS1OySxqngB4sM9qZXbAA9YvzpER1AXIw/vvrBFRGRZqqz2nj76y18vzQFqE8WRAZ7ExHijZe7C26uFlxdzLgf+DvIz4Pu0f70iPY/oZJCm3bl8cpnG8naX47FbOLac/tx3slxTj0LRtpeeWUteUWVJO0tYOnGTDbszGt8LKF7EOeN68Go/pHNXhzZMAxq62y4WMxtVt7RMAy27M7nf99uYVdGMS4WE/++YTSD4kPb5PlFROTIDMNgV0YRi9ZlsGT9PgpLq5s8Hhftz+BeofSLC6ZPt6DjGsFttRns2VfEuqRc1iblkpxawJ/7vYL8POjfI5izRnejX1yw2lvSZjJyS5m/Mo2qmjrq6myUlNeQV1jJ3uySJjO3EroHMfmkOEYNiGzWWqs2m8G65Fy+XbKHdcm5TR7zdHehS7gvXSJ8iT3w98CeIbi6HN860PVtO5N+b0SkQ7HZDH5YlsKnP+84pP1xsNBAT3rFBhDo64HNMCgqrWZvVglZ+w+tXjesbzinDo1lREL4cb+nNqiptbI9pYDd+4qotdrwcHMhLsqfHjEn1tfUEVitNjbu3M/iDRnsSCtkZL9Irj4nwWHxtPtk2fs/bOOzX3Ye9rHoUB8G9AxhQI9g+sUFt+vFREVEpOPYuCOPjxYkN651eSxmE3SL9Kdv9yD6dAsioVsQoYGeR/0SabMZbNyZx/dLU1i5tX42W2igJ/+4aliHm8UjnVNqdglfLdrFb+syGkfhhwZ6Mrp/JIPjQ4kN98Xb05W6Ohs5hRVk5pWRnlNGanYJqVn1A5usNgOzCfx83OkS7kuv2AB6xgbQIzqA8CCvYybRauusFJXWUFRWRXFZDSXl1dTW2aizGlhtNqxWA6vNoM5qI2t/Odv3FjR+kfHxdOWBq4czqJcSZSIi7Y3VamPz7v2sTcplw4489maVHLJPdKgPcdH+hAR4EuzvgYebBYu5vpO+ts524I+Vmjob+cVV7MstY1dGIZXV1j+dx5t+cSH0iwsioXsw4UFe6uiXdqWyuo6NO/NYuCadVVuzG2c2BPq6M2l0N04dGkNksHeTn1vDMMjKL2fJhn38siq9cRkSkwmG9glnzIBIBvYKJewY30lERJxJTa2VxeszWL09h9yCCrw9XQkL9KJvtyAG9Aw5YhuhvLKWpNQCNuzIY21SbuP68gDenq6M7BfBqP6RJPYOxcPN5ZhxGIZBWk4p65PzWL8jly2786mptR6yn4vFRL+4YIb1DWdY33CiQ306xXu61WbUD9LdlMmSDfsoOiiBmRgfyn9uGuOw2Np9siwzr4xvluzBYjHh4+lGkJ87XSP8GjtoRERE7KWwtIr0nFJy8iuoqrE2dsjU1FqpqbWRnV/Onsxi8gorDzk22N+D7lH+BPt7EOzngdVmUFldR0VVHfuLK9mVXkRZZS0AZrOJs0d344pJfTSVX9qd/OJKfly2lx+W7aW0oqbVzuvmYiY6zIeQAE883V2wWg2qaup/R4rLqikuq6a8qq7F5/V0tzAuMYbLJvbWQCoRkQ6isKSKjbv2s2lnXuN6IcfLy8OFQb1CGdI7jCF9wuyyFpSIveQXVzJvRSo/Ld/bZPZDkJ87EcHe+Hi6UVFdS2ZeOQUlf1Rc8vZw4YyRXTnnpO4qPS0iYmepWSX8ujad39ZlsP+g6ncuFjM9ov3pGulHgK87/t5uWCxmrDYbtbU2Ckqq2JdXxq6MIorLmn63DvR1p3+PEDzdXSitqGFXRtEhfU3hQV7ERfsTFeKNr5cbPl6uuLtaMJlMmM0H/phoXF6hMeljgHHgf4bxxwMGxmH2NRr/Xf/YH8cZB5+wYduR9v3T+aqq6ygoqSYtu4RdGUWUVtQ2XpevlxsnD45iZP9I+scF4+Z6YjP1TkS7T5aJiIi0d/nFlWzfW8D2lAK27S1gz77iwy6C/Wfenq6ckhjNOSd1p0vE8a9NINIWqmutrEvKYdXWHHamF5K5v5zaOhtQnxyODvUhOtSHrhG+dI30IyLYGw93F2pqreQXV7JnX32jeFd6IXuzSqmz2pr1vC4WE/4+7vV/vN1wc7VgsZiwmM0H/jbhYjET7O9J9yg/BvYM6fSlKkREOruS8hqSUgvIzCsjv7iK/OIqamqtWG0GNsPA1WLG1aXhj4VAX3ciQ7zpERNAbLhvs0sGi7RXtXU2lm/O5KflqWzfm99krb0GLhYTCd2DOW14LGMGROHhfuzZDCIi0nqsNoNtKfms2JLFis1Z5B5mIPWRuLmY6RcXXL8GWu8wukb4HjJrLDOvjNXbc1izPYctu/Ob/R26I/DxdGVYQjjjBkeT2DsMl2asodkWlCwTERFpZVXVdexML2LfgQ6ewtIqXCxmvDxc8HR3wc/bnR4x/nSN8GvWOgQi7ZHNZmAYBmZzy9etsFrrSzdm5JRRWFpNZXUtLhYzHm4WPN1d8fNxI8DHnUBfd7w9XTtFqQkRERGR41Fda2VPRjH5JZWUVdTi7eFKkL8HPWMDcHfg6HsREflDQ3ncHWlFZOeXU1xaTVFZNYZRX03IxWIiyM+D0EAvesb40z3Kv0UzqCqr69i+t6C++lFBBWUVNZRV1lJba8Nm1A8mqv+O/scxJhNNvks3/NOEqcn/D3ms8d8NjzXd9ufv5/UPH+WcJhPurhYCfN2JCvWhR7Q/cdH+7SZBdjAly0RERERERERERERERMRptb/0nYiIiIiIiIiIiIiIiEgbUbJMREREREREREREREREnJaSZSIiIiIiIiIiIiIiIuK0lCwTERERERERERERERERp6VkmYiIiIiIiIiIiIiIiDgtJctERERERERERERERETEaSlZJiIiIiIiIiIiIiIiIk5LyTIRERERERERERERERFxWkqWiYiIiIiIiIiIiIiIiNNSskxERERERERERERERESclpJlIiIiIiIiIiIiIiIi4rSULBMRERERERERERERERGnpWSZiIiIiIiIiIiIiIiIOC0ly0RERERERERERERERMRpubTWid59912Ki4tb63QiIiLSDvj7+3PNNdc4OgxBbS0REZHOSu2t9kPtLRERkc6pOe0tu8wsMwyDqqoqDMOwx+nFzvT6dVx67To2vX4dm14/6Wz0M30o3ZPD0305PN2Xw9N9OZTuyeHpvoiz0+/AsekeNY/u07HpHjWP7tOx6R41T3u9TybDDhFlZWXx5ptvMm3aNCIjI1v79GJnev06Lr12HZtev45Nr590NvqZPpTuyeHpvhye7svh6b4cSvfk8HRfxNnpd+DYdI+aR/fp2HSPmkf36dh0j5qnvd4nrVkmIiIiIiIiIiIiIiIiTkvJMhEREREREREREREREXFadkmW+fj4cMopp+Dj42OP04ud6fXruPTadWx6/To2vX7S2ehn+lC6J4en+3J4ui+Hp/tyKN2Tw9N9EWen34Fj0z1qHt2nY9M9ah7dp2PTPWqe9nqf7LJmmYiIiIiIiIiIiIiIiEhHoDKMIiIiIiIiIiIiIiIi4rSULBMRERERERERERERERGnpWSZiIiIiIiIiIiIiIiIOC0ly0RERERERERERERERMRpnXCy7I033uCqq6466j61tbU899xznHzyyQwePJgrr7yS7du3n+hTSytozuuXn5/PPffcw6hRoxg5ciR33303OTk5bRShHKyoqIhHHnmEcePGMWTIEC677DLWrFlzxP0zMjK46aabGDJkCGPHjuXFF1/EarW2YcRysJa+fuvWreOqq65i6NChnHzyyTz88MMUFRW1XcDSREtfv4PNnDmT3r172zlCkSOz2Wy8/PLLjW2xG2+8kfT09GYd+80339C7d28yMjKanO/tt9/mzDPPZPDgwZxzzjl89tln9grfblr7vlitVl5++WXGjx/PwIEDufDCC1m0aJGdoref1r4vB6upqeHcc8/lgQceaM2Q24Q97svEiRPp3bt3kz8d6d7Y455s2rSJK664goEDB3LKKafw8ssvY7PZ7BG+3bT2ffnzz8jBfzIzM+11Ga3OHj8v33//PZMnT2bQoEGcffbZzJ071w6Ri9hfc/pmCgsLueeeexg+fDgjRozg0UcfpbKyso0idLzm3KOdO3cybdo0Ro4cyejRo7nzzjs71Ptka2jOfTrYsdpunZH6sptHfcaHp77Z5umwfaDGCZgzZ47Rp08f48orrzzqfg899JAxZswYY/HixcauXbuMO+64wzjppJOMkpKSE3l6OUHNff2uvPJK49JLLzW2bdtmbN261bj44ouNiy66qI2ilINde+21xuTJk43Vq1cbe/bsMR599FFj4MCBxu7duw/Zt6amxpg4caIxbdo0Izk52ViwYIExYsQI46WXXnJA5GIYLXv99uzZYwwePNh47LHHjF27dhmrV682Jk+ebEydOtUBkYthtOz1O9jGjRuNhIQEIz4+vo0iFTnUjBkzjJEjRxq//vqrsX37duO6664zJk6caFRXVx/1uIyMDGPo0KFGfHy8kZ6e3rj9tddeM4YNG2Z8//33RmpqqvHxxx8bCQkJxldffWXnK2ldrX1fnnvuOWPUqFHGr7/+aqSlpRmvvfaa0bdvX2Pz5s32vpRW1dr35WCPPfaYER8fb/zjH/+wR+h21dr3pby83OjTp4/x66+/Grm5uY1/OtJ3pNa+J3v27DEGDRpk/POf/zRSUlKMn376yUhMTDTefPNNe19Kq2rt+3Lwz0dubq6xc+dOY+TIkcb9999v70tpVa19X5YvX24kJCQYH330kZGWltb4/XbRokX2vhSRVtWSvpmLLrrI2LJli7Fs2TJj/PjxHe594Hg15x4VFBQYJ510knHHHXcYycnJxubNm40rrrjCOOuss4yqqqo2jNZxmvuz1KA5bbfORn3ZzaM+4yNT32zzdNQ+0ONKlmVnZxs33XSTMXjwYGPSpElH/cVJS0szevfubfz666+N24qLi43x48cby5YtO56nlxPUktevuLjYiI+PN3755ZfGbT///LMRHx9vFBYWtkG00mDv3r1GfHy8sWbNmsZtNpvNOP30040XX3zxkP2//fZbo3///kZRUVHjto8//tgYMmTIMb+QSutr6ev3/PPPGxMnTjRsNlvjttWrVxvx8fFGWlpam8Qsf2jp69egvLzcmDhxojF16lQly8RhqqurjcTEROODDz5o3FZcXGwMHDjQ+Pbbb494nNVqNS677LLGn9+Dv0CffPLJxmuvvdZk/wcffNC4/PLLW/8C7MQe9+Wpp5465Nhhw4YZb731VutfgJ3Y4740WLx4sTFmzBjjnHPO6XDJMnvcl40bNxrx8fFN2modiT3uyT/+8Q/joosuatL+eemll4ybb77ZPhdhB/b8HWpwxx13GJMmTepQbXp73JfHH3/cuOCCC5rsP2XKFOOxxx5r/QsQsYOW9M2sW7fOiI+PN3bt2tW4bcmSJUbv3r2N7OzstgjXIVpyjz799FMjMTHRqKysbNyWmZlpxMfHd/r+x5bcpwYt+dzpDNSX3TzqMz469c02T0fuAz2uMoxbt27F1dWVb775hkGDBh1136VLl+Lr68u4ceMat/n5+bFw4UJGjx59PE8vJ6glr5+Hhwfe3t7MnTuXsrIyysrK+Prrr+nevTt+fn5tFLEABAYG8uabbzJgwIDGbSaTCZPJRElJySH7r1mzhn79+uHv79+4bdSoUZSVlTnd1PH2oKWv33nnncfTTz+NyWRqsj9AcXGx/QOWJlr6+jX473//S3x8POeff35bhClyWElJSZSXlzdpd/n5+ZGQkMDq1auPeNzrr79ObW0tN910U5PtNpuNp59+mgsuuKDJdrPZfNTfh/amte8LwD/+8Q8mT54MQFVVFbNnz6ayspKRI0e2/gXYiT3uC0BBQQEPPvggjz32GIGBga0et73Z474kJycTEhLSpK3Wkdjjnvz+++9Mnjy5SfvnzjvvZObMma0bvB3Z63eowe+//878+fN57LHHcHNza7W47c0e9yU4OJidO3eyYsUKDMNg5cqV7N69m4EDB9rlGkRaW0v6ZtasWUNoaCg9evRo3DZixAhMJhNr1661d6gO05J7NHr0aF577TU8PDwat5nN9d2eHamNejxacp8aNPdzp7NQX3bzqM/46NQ32zwduQ/U5XgOmjBhAhMmTGjWvikpKcTGxjJ//nzefPNNcnJySEhI4IEHHmjyIS9tpyWvn5ubG0899RSPPPIIw4YNw2QyERYWxpw5cxobHdI2/Pz8OOWUU5psmzdvHqmpqTz00EOH7J+dnU1ERESTbWFhYQBkZWU1uwElraOlr9/h3h/feustQkNDtfaVA7T09QOYP38+v/32G99++y2//vprW4QpcljZ2dkAREZGNtkeFhbW+Nifbdq0if/97398/vnnh9ScN5vNh3xJzMzM5Pvvv+fSSy9txcjtq7Xvy8G++eYb7r//fgzD4I477mjyJaG9s9d9efjhhxk/fjwTJkzgnXfead2g24A97ktycjJeXl7ceeedrFu3jsDAQC666CKmTp3aIdrZrX1PysrKyMvLw9fXl4ceeojFixfj5+fHlClTuP7667FYLPa5kFZmz/cWgOeff57TTjuNYcOGtU7AbcQe9+Wqq65i06ZNXH311VgsFqxWKzfffDPnnXde61+AiB20pG8mJyfnkN8fNzc3AgICyMrKskd47UJL7lFMTAwxMTFNtr355pt4eHgwfPhwe4TXbrTkPkHLPnc6C/VlN4/6jI9OfbPN05H7QO3+k1tWVkZqaiqvvfYaf//735k5cyYuLi5cfvnl5Ofn2/vp5QQZhsH27dtJTEzkgw8+4L333iMqKopbb72VsrIyR4fn1NatW8eDDz7IxIkTOfXUUw95vKqq6pDRpu7u7gBUV1e3RYhyFMd6/f7s6aefZtGiRfz73//G1dXV/gHKUR3r9cvJyeGRRx7hiSee6JAzKKRzaVj4/XCfCYf7PKioqODee+/l3nvvpVu3bsc8//79+7nxxhsJDg7mlltuaZWY24I978vw4cOZO3cu999/PzNnzuTDDz9stbjtzR735eOPP2b37t08+OCDrR5vW7HHfdm5cyclJSWceeaZzJo1i8suu4yXXnqJGTNmtHr89tDa96Thu8XTTz9NVFQUb731FjfccANvvPFGh7knYN/3ltWrV7N161ZuvfXWVou3rdjjvmRlZVFYWMgjjzzCF198wQMPPMA777zD559/3urxizhaZWXlYWeTHul3SGD27NnMmTOHe++9l6CgIEeH0260tK3vjNSX3TzqM1bfbHN1pD7Q45pZ1qIncHGhrKyMF154oTFL+MILL3DKKafw1VdfccMNN9g7BDkBP/74I3PmzOHXX3/Fx8cHqJ+qPX78eD7//HOuueYaxwbopH7++WfuvfdehgwZwrPPPnvYfTw8PKipqWmyreGN2MvLy+4xypE15/VrUFtbyyOPPMLcuXN57LHHOP3009soSjmSY71+hmHwwAMPcNZZZzUp2yDiKA2laGpqapqUpamursbT0/OQ/R9//HG6d+/erFlie/bsYdq0aVitVt5///0OVW7DnvclMjKSyMhI+vTpQ2pqKrNmzeLyyy9vveDtqLXvy549e5g+fTqzZs3q0O0Pe/y8vPXWW1RXV+Pr6wtA7969KSsrY+bMmdxxxx3tfkRua98TF5f6r6Zjxozh9ttvB6Bv374UFBTw6quvctdddzUpzdJe2fO95auvvmLgwIH069ev9QJuI/a4L3fccQeTJ0/miiuuAOp/XoqLi5k+fToXXnhhu/8dEmmJw32/h/rfoY78+WoPhmHw0ksvMXPmTG655RauuuoqR4fUrrTkc8dZqS+7eZy9z1h9s83T0fpA7Z4si4iIwMXFpcl0Og8PD2JjY8nIyLD308sJWrNmDd27d2980wPw9/ene/fupKamOjAy5zVnzhz++9//MmnSJJ5++ukjrlUQERHBjh07mmzLzc0FIDw83O5xyuE19/WD+tFMt99+O2vWrOH555/nrLPOasNI5XCa8/plZmaybNky1q1bx9y5cwGoq6sDIDExkUcffVTlgaRNNZTsyc3NpUuXLo3bc3NzD1vS4IsvvsDNzY3ExEQArFYrAJMnT+bmm2/m5ptvBmDt2rXccssthIeH8/bbb3e4z5bWvi833HADixYtIiEhgaioqMbjevfuzZdffmnPS2lVrX1f6urqKC8v59prr208pqqqinXr1jFv3jzWr19vz8tpNfb4PXJzczvkcyQ+Pp6KigqKi4vb/czk1r4nN954I+7u7sTHxzc5rlevXlRUVFBQUEBwcLC9LqfV2Os912azsXDhwg45qwxa/75cfPHF7Nmz55Ayt4MHD2bmzJkUFRVpJol0KhEREfz8889NttXU1FBUVNRY0kvqO1offPBBvvvuOx588MFO31l/PJr7uePM1JfdPM7cZ6y+2ebpiH2gdk+WDR8+nLq6OjZv3tzYkK2qqiI9PZ1zzjnH3k8vJygiIoLvv/+e6urqxmmiFRUVZGRkqLPXAT788EMee+wxrrrqKh5++OGjjq5tKAFVVlbW+MG1YsUKvL296dOnT1uFLAdpyetXU1PDTTfdxPbt25k1axYjR45sw0jlcJr7+oWHhzN//vwm2+bPn8+zzz7L3LlzO0RHn3Quffr0wcfHh5UrVzZ2UJaUlLBt2zauvPLKQ/b/88/vxo0bue+++3jzzTcbO7E3bdrEDTfcQEJCAjNnzuxQM8oatPZ9sVgs/POf/+Qvf/kL99xzT5P9evbsad+LaUX2+Hk599xzm+xz7733EhERwb333munq2h9rX1fDMPgjDPOYMqUKY2zqAA2b95MaGhou0+UgX1+h4YMGcLGjRub7JecnIyfnx8BAQF2u5bWZI/fIYBdu3ZRWFjImDFj7HsBdtLa98XX1xdPT0+Sk5ObzORv+HlRokw6m+HDh/Pss8+SmppK165dAVi1ahUAQ4cOdWRo7cr999/PggULeO6559TneATN/dxxZurLbh5n7TNW32zzdNQ+0FZPllmtVgoKCvD19cXDw4Nhw4YxZswY/vGPf/Cf//yHgIAAXn75ZSwWC+eff35rP72coD+/flOmTGHWrFn87W9/46677gLgxRdfxN3dnQsvvNDB0TqXlJQUnnjiCc444wxuuukm9u/f3/iYh4cH7u7uFBcX4+/vj5ubG6effjovvvgif/vb37j33nvJyMjg+eef57rrrjtqJl/so6Wv3xtvvMHatWt57rnniIuLIy8vr3H/hn2k7bT09Wv4AtugIUH25+0ibcHNzY0rr7ySZ599lqCgIKKjo5k+fToRERFMnDjxkM/+P/+cZmdnAxAVFUVAQAB1dXXce++9BAcH89RTT1FdXd34HmWxWDpMB2Vr3xeA6667jldeeYX4+HgGDBjA/Pnz+e677zrUekv2uC9/TnJ4eHjg7e3dod4T7XFfzjjjDGbNmkVcXBz9+/dn+fLlvP322zz88MNtfXnHxR735JZbbuHaa69lxowZnH/++WzZsoU333yTa665BovF0taXeFzscV8Atm3bhqurK3FxcW15Oa3GHvdl6tSpzJw5k9DQUIYOHcratWt54403uO2229r68kRa3Z9/JwYNGsSQIUO4++67+fe//01FRQWPPPIIU6ZMcYrZCYfz53v05Zdf8sMPP3D//fczYsSIJt+hG/ZxRsf7ueNM1JfdPOozVt9sc3XkPtBWT5ZlZWVx2mmn8eSTTzb+YsyYMYNnn32W22+/naqqKoYMGcL777/fYTpTnMmfX7+wsDA+/PBDpk+fztVXX43ZbGbYsGF8+OGHjesrSNuYN28etbW1LFiwgAULFjR57IILLuCCCy5g6tSpvP/++4wcORJ3d3fefvttHn30US6++GL8/f25/PLLO2zplo6upa/fd999h2EY/P3vfz/kXA37SNtp6esn0t7ceeed1NXV8X//939UVVUxfPhwZs2ahaurKxkZGYe03Y5m06ZNjWU1/lxDPDo6moULF9rlGuyhNe8LwPXXX4+rqyszZswgKyuLuLg4Xn75ZU477TQ7X0nrau370lm09n2555578PHx4fnnnyc7O5uYmBgefvhhLr74YjtfSetp7XsycuRI3njjDV544QXeeOMNQkNDmTZtWodbG8Qev0N5eXn4+/t36HW4Wvu+3HXXXQQGBvLGG2+QlZVFTEwM9913n9bhkU7hz30zJpOJV155hUcffZSrr74ad3d3Jk2axIMPPujoUB3mz/fou+++A+CZZ57hmWeeabKvM7ZbGhyun1aaUl9286jPWH2zzdWR+0BNhmEYbfZsIiIiIiIiIiIiIiIiIu1Ixx2WJiIiIiIiIiIiIiIiInKClCwTERERERERERERERERp6VkmYiIiIiIiIiIiIiIiDgtJctERERERERERERERETEaSlZJiIiIiIiIiIiIiIiIk5LyTIRERERERERERERERFxWkqWiYiIiIiIiIiIiIiIiNNSskxERERERERERERERESclpJlIiIiIiIiIiIiIiIi4rSULBMRERERERERERERERGnpWSZiIiIiIiIiIiIiIiIOC0ly0RERERERERERERERMRpKVkmIiIiIiIiIiIiIiIiTkvJMhEREREREREREREREXFaSpaJiIiIiIiIiIiIiIiI01KyTERERERERERERERERJyWkmUiIiIiIiIiIiIiIiLitJQsExEREREREREREREREaelZJmIiIiIiIiIiIiIiIg4LSXLRERERERERERERERExGkpWSYiIiIiIiIiIiIiIiJOS8kyERERERERERERERERcVpKlomIiIiIiIiIiIiIiIjTUrJMREREREREREREREREnJaSZSIiIiIiIiIiIiIiIuK0lCwTERERERERERERERERp6VkmYiIiIiIiIiIiIiIiDgtJctERERERERERERERETEaSlZJiIiIiIiIiIiIiIiIk5LyTIRERERERERERERERFxWkqWiYiIiIiIiIiIiIiIiNNSskxERERERERERERERESclpJlIiIiIiIiIiIiIiIi4rSULBMRERERERERERERERGnpWSZiIiIiIiIiIiIiIiIOC0ly0RERERERERERERERMRpKVkmIi2WkZFB7969+fLLLx0dioiIiIhTuOqqq7jqqqscHYaIiIiIiEinpGSZiIiIiIiIiIiIiIiIOC0ly0RERERERERERERERMRpuTg6ABFxvC1btjB9+nS2bNmCzWZj0KBB/O1vf2Pw4MEAzJ8/n1deeYW9e/fSo0cPbrvttkPOkZSUxCuvvMKaNWsoLS0lKCiIM888k3vvvRcPD482viIRERGRjmHChAmcfvrpJCcns379es4991xuu+02nnjiCZYvX46Hhwc33HCDo8MUERER6fBWrlzJ1KlTD/vYiBEjmD17dhtHJCLtiZJlIk6urKyMG264gVGjRjFjxgxqamqYOXMm119/PYsWLWL16tXceeednHvuudx3331s376d++67r8k5cnNzueKKKxg8eDBPPfUUbm5uLF68mHfeeYewsDCmTZvmoKsTERERaf8++OADrr32Wm688UY8PT258sorcXFx4bHHHsNsNvPyyy+TlpZGYmKio0MVERER6bD69evHJ5980mTbd999x+zZs/nLX/7ioKhEpL1QskzEye3atYvCwkKmTp3KkCFDAIiLi+OTTz6hvLycV199lYEDBzJ9+nQATj75ZACee+65xnPs2LGDvn378tJLL+Hj4wPAmDFjWLp0KStXrlSyTEREROQooqKiuPfee4H6xFlmZibfffcdPXv2BGDQoEGcccYZjgxRREREpMPz8fFprKIEsHHjRj799FOuueYazj//fMcFJiLtgtYsE3FyvXr1IigoiJtvvplHHnmEBQsWEBISwn333UdAQABbt25l/PjxTY4566yzmvx/7NixzJkzB3d3d3bt2sUvv/zCzJkzKSgooKampi0vR0RERKTD6du3b+O/16xZQ5cuXRoTZQCRkZFNOnZERERE5MRkZ2dz2223kZiYyP333+/ocESkHdDMMhEn5+3tzQcffMDMmTP58ccf+eSTT/Dw8OD888/npptuwjAMAgMDmxwTFhbW5P82m43nn3+eDz74gIqKCiIjIxk4cCDu7u5teSkiIiIiHZKXl1fjv4uLiw9pewGEhoayf//+tgxLREREpFOqrKzk1ltvxc3NjRdffBGLxeLokESkHVCyTESIi4tj+vTpWK1WNm3axNdff81HH31EeHg4ZrP5kI6ZoqKiJv9/8803effdd3n00UeZOHEivr6+AKr3LCIiItJCgYGBpKamHrL9z+0vEREREWk5wzB44IEH2LNnDx999NFhBymJiHNSGUYRJ/fTTz8xatQo8vLysFgsJCYm8u9//xs/Pz/y8/NJTExk/vz5GIbReMzChQubnGPt2rX07NmTiy66qDFRlpOTw44dO7DZbG16PSIiIiId2ahRo8jIyGDz5s2N2woKCtiwYYPjghIRERHpJF555RV++uknHn/88SalsEVENLNMxMkNGTIEm83GbbfdxrRp0/D29ubHH3+ktLSUiRMncvbZZ3P11Vdz++23c8kll5CSksLrr7/e5BwDBw7ktdde480332Tw4MGkpqbyxhtvUFNTQ2VlpYOuTERERKTjOf/883n//fe5/fbbufvuu/Hx8WHmzJkagCQiIiJygubPn8+rr77K5MmTiYuLY+PGjU0Gh2uNWBHnpmSZiJMLCwvj7bff5qWXXuLhhx+msrKSXr16MWPGDEaNGgXAW2+9xfPPP8/tt99OTEwMTzzxBDfffHPjOW666SYKCwt5//33efXVV4mMjOT888/HZDLxxhtvUFJSgp+fn6MuUURERKTDcHNz47333uOJJ57gv//9LyaTiYsvvpjY2Fjy8/MdHZ6IiIhIh7Vw4UIMw+C7777ju+++O+Tx5ORkB0QlIu2FyTg4fS4iIiIiIiIiIiIiIiLiRLRmmYiIiIiIiIiIiIiIiDgtJctERERERERERERERETEaSlZJiIiIiIiIiIiIiIiIk5LyTIRERERERERERERERFxWkqWiYiIiIiIiIiIiIiIiNNSskxERERERERERERERESclpJlIiIiIiIiIiIiIiIi4rSULBMRERERERERERERERGnpWSZiIiIiIiIiIiIiIiIOC0ly0RERERERERERERERMRpKVkmIiIiIiIiIiIiIiIiTkvJMhEREREREREREREREXFaSpaJiIiIiIiIiIiIiIiI01KyTERERERERERERERERJyWkmUiIiIiIiIiIiIiIiLitJQsExEREREREREREREREaelZJmIiIiIiIiIiIiIiIg4LSXLRERERERERERERERExGkpWSYiIiIiIiIiIiIiIiJOS8kyERERERERERERERERcVpKlomIiIiIiIiIiIiIiIjTUrJMREREREREREREREREnJaSZSIiIiIiIiIiIiIiIuK0XBwdgDjO6m3ZvPf9Nrw8XLntL4PoGunn6JBEREREBDAMg7m/7Wbx+gxiw3259tx+BPp6ODosEREREZFOo6bWypyfklifnEu/uGCumZyAh5u6y0WclckwDMPRQUjbS8ks5p6XFlNbZwOge5QfL/ztFCwWTTYUERERcbTPftnB+z9sb/x/jxh/nrtznNpqIiIiIiKt5I2vNvHd7ymN/z9zVFdu/+tgxwUkIg6lb9tO6qtFu6itsxEe5IWri5mUzBIWb9jn6LBEREREnF5mXhlzfkoCYFxiNF4eLuzOKOb7pSnHOFJERERERJqjrKKG+SvTABieEI7JBPNWpLIjrdDBkYmIoyhZ5oTKKmpYujETgPuuHMpF43sBsETJMhERERGH+3BeMjabwbC+4dx35TCuOScBgG+W7MFmU1EIEREREZET9cuadGpqrXSL9OOf143k1CExAHy9eLeDIxMRR1GyzAmt3JpNTZ2NrhG+xHcJZOzgKADWJ+dRVlnr4OhEREREnFdxWTVLNtYPYLpiUh8Axg+LxcvDhZyCCjbtynNkeCIiIiIincKyTfUTCSaO7IrJZOK8cT0AWLoxk8LSKkeGJiIOomSZE1qXnAvAyP6RmEwmukb4ERPmQ53Vxqad6oARERERcZQlG/Zhsxn0jA2gZ0wAAB5uLpySWD/SdfF6VQIQERERETkRRaXVbN9bAMCo/pEA9IwJoFdsAFaboepbIk5KyTInY7MZbNhRnxAb0juscfuAHiEAjR8UIiIiItL2GpJh4w+UgWkwekD9l/g123NUilFERERE5ASs2Z6DYUCPGH9CAz0bt48fGgvAr2szHBWaiDiQkmVOZk9mMSXlNXh5uNC7a2Dj9r7dgwDYnqJkmYiIiIgjlFbUkJxa3xYbMzCqyWP9ewTj6W6hsLSa3fuKHBCdiIiIiEjnsHVPPgCJ8WFNtp88OBqz2cSu9CLSc0odEZqIOJCSZU5mW0r9h0FC92BcLH+8/H271SfLdu8rorrW6pDYRERERJzZpp37sRkQG+5LSIBnk8dcXSwMPvBlfn2yymaLiIiIiByvhv7RfnHBTbYH+Lo3VuL6bZ1ml4k4GyXLnMy2AzPHEg7MJGsQHuRFgK87dVaDlMxiR4QmIiIi4tQa1pU9uFT2wfr3qP8yv/XAl3sREREREWmZwtIqMveXYzJBn25Bhzw+fmh9OfRf12Wo/LmIk1GyzIkYhsH2g2aWHcxkMtE90g+A1KySNo9NRERExJkZhsH6HfXJssTeoYfdp9+B9lvS3gKs+uIuIiIiItJiSXsLAega4YePp+shj4/oF4Gnuwu5BRVs36vlakSciZJlTiS3sJKCkmpcLCZ6xgYc8njXA8myvZlKlomIiIi0pX15ZeQVVuLqYj6kHEyDblH+eLq7UFFVx15VAhARERERabHdGUUA9DpM3yiAh5sLYwZGArBIpRhFnIqSZU5kV3oRUJ8Uc3e1HPJ496gDybJsJctERERE2lJDCcZ+3YPxcHM57D4Ws4neXQMB2JFW2GaxiYiIiIh0FrsOJMt6xAQccZ/xQ2IB+H3DPmrrrG0QlYi0B0qWOZGGD4OeR/gw6BbpD9TPLDMMlfYRERERaStbdteXyh4Uf/gSjA0aRsDuPDAISkREREREmscwDHZn1Fdo6BHjf8T9+vcMIdjfg7LKWtZsz2mr8ETEwZQscyINM8uONM04NtwHkwnKKmspKq1uu8BEREREnJhhGI3rIfTrfvgSjA16xdbPLGsYBCUiIiIiIs1TUFJFUVk1ZrOJ7lFHTpZZzCZOSYwB4KflqW0Vnog4mJJlTsIwDHYeY5qxq4uF0ABPALLyy9soMhERERHnllNQQVFpNS4W81FHuMIfg55Ss0uprlVJGBERERGR5mqYVRYb5nPYJWoOdtaYbpjNJtYl56oEuoiTULLMSWTnV1BeWYuLxUzXCL8j7hcZ4n1gfyXLRERERNpCw6yyHjH+uB3jS3uwvwcBPu7YbAZ7M4vbIjwRERERkU6hOeuVNYgI9uaUxGgAZn65iTqrzY6RiUh7oGSZk2j4MOge5Yery5Ff9ojg+mRZ5n4ly0RERETaQkOyrG+3oGPuazKZ6BZZP/ApLbvUrnGJiIiIiHQmzVmv7GBXn5OAj6cru9KLeOHDddTWqbKDSGemZJmTaFivrOcR1itrEHVgZlmWkmUiIiIibSLpQLKsTzOSZQBdIn2B+lKMIiIiIiLSPA2TCXo2Y2YZQLC/J3dfPgSL2cTiDfu456XFbNyRZ78ARcShlCxzEs39MGiYWaYyjCIiIiL2V1FVS2pWCQB9ugY265iGktqp2SV2i0tEREREpDMpLKmioKQKkwm6RzVvZhnAiIQIHrl+FL5ebqRklvB/byzjnW+3YhiGHaMVEUdQsswJ2GxGs5NlkZpZJiIiItJmdqYVYTMgLNCTYH/PZh3TNaJ+ZlmakmUiIiIiIs2y80DVrdhwXzzdXVp07JA+Ybx2/wTOHtMNgC8X7eL3DZmtHKGIOJqSZU4gc38ZFVV1uLmY6XKgc+VIIg/MLCutqKWsoqYtwhMRERFxWslphQD07tq8EoxQ/wUfoKCkmlK110REREREjmnHgXZ3r2MsUXMkAb7u3HLRIC6b2BuAN+dupqZWa5iJdCZKljmBhpETcdH+uFiO/pJ7uLsQ6OsOQJZKMYqIiIjYVUvXTQDw8nAlLLB+Flqa1i0TERERESdWWV3XrOVkGvpHe8U2r/T5kVx8ejyhgZ4UlVXz69r0EzqXiLQvSpY5gV0NHwZdmvdhoFKMIiIiIm1jd0OyLLb56yYAdNG6ZSIiIiLi5DbsyGXaEz9z4xM/M+fH7UdcR8wwDHam188si+8ScELP6WIxc97JPQD4fmnKCZ1LRNoXJcucQMPIieaOWI44UIpRM8tERERE7KekvIbcwkoAekQHtOjYhnXLUrOULBMRERER55NfXMnT76+hqKwagE9+3sHSTYdfRyw7v4LSilpcLGa6RbZskNrhnDY8FrPZREpmSbNmtYlIx6BkWSdntdrYva8YaH5N3ijNLBMRERGxu4YSjJEh3nh7urbo2D9mlqkMo4iIiIg4nw9+SqKsspYeMf5ccGpPAN7+esth1xFrmFXWPcoPV5cT7w739XKjf1wwACu2ZJ3w+USkfVCyrJNLyymlptaKp7sL0aE+zTqmcWaZkmUiIiIidrP7ONYra9Awsywtu+SI5WZERERERDqjyuo6lmzYB8CN5w/gykl9CPH3IL+4it837jtk/4aqW/HNXKKmOUb1jwRg7fbcVjuniDiWkmWd3MElGM1mU7OOaVizLKegwl5hiYiIiDi9XY3JspaXgokJ98VkgtKKWorLalo5MhERERGR9mvZpkyqaqxEhXiT0D0IN1cLZ5/UHYBvl+w5ZDDZjrT6mWXNrbrVHP171M8sS04rxGrT4DWRzkDJslaUV1jJ8s1ZrNiSRfGBernHK7+4knkrUvlwXhLLN2cedgpxczQky1ryYRAW6AVAQUkVtXW243peERERETm6XRn1pbJ7HMfMMndXC6EH2mz78spaMywRERERkXZt5dZsAE4dEoPJVD85YOLIrri6mNmVUUxyamHjvlU1dexIKwKgd9fWm1nWJdwXDzcLldV1ZOSqNLpIZ+Di6AA6g6rqOmZ+uYlf16bTMHDBbIKEuGBOGhjFqUNi8PFya9a58gormfPTdhatTefgQQkBPu7cdWkiw/qGtyi27Sn5AMS34MPA38cNN1cLNbVW9hdVNs40ExEREZHWUVJeQ+6BWfzHkywDiAn1IbeggozcUvodWDNBRERERKQzs1ptbNqZB8DQg/pJ/X3cOSUxhp9Xp/Htkj306RYEwLaUAuqsNkL8PZq9RE1zWCxmesYGsGV3PjtSC+l6YE1hEem4NLPsBNXW2fj32ytYuKY+URYX7U+3SD9sBmzZnc8bX23m6v/M57kP1/LL6rTGTpE/S88pZc5P27nlmV9YuKY+Uda7ayAThsUSEuBJUVk1j81awapt2c2OrbisunHR9/4t6EAxmUyEBXoCHDFeERERETl+DeuVRQZ74+PpelzniAmr/7KfkauZZSIiIiLSftXUWlm0LoPF6zOoqKo9oXMlpxVSXlWHr5frIYPOJo+tL8W4dFMm+cWVAGzYUZ9YGxwf1jgLrbX0PrAG2o4Dlb1EpGPTzLIT9PGCZLbuycfbw4X/u24k/XuEAPVJpmWbM/l5VRqp2aUsWpvBorUZAIQFedG7SyDRoT7kF1eyLaWgSfmchO5BXH9e/8ZFJ2vrrLz86QYWrc3gmdlreOrWsfRsRlnFbSkFAMSG++Dv496i6woL8iIjt4ycQiXLRERERFpbw3plPY5jvbIG0QeSZSrDKCIiIiLtVWFJFf945Xey8ssBiAzx5j/TRhMRfHyVrNYl5wL1yS+LuWnyq0dMAP3igtm6J58flu3l8jP7sGxTJgCJvUNP4CoOr3tUfVs+Nauk1c8tIm1PybITkJ1fzhcLdwJw+8WDGxNlUJ9smnJKT84f14NtKQWs2Z7D5t372ZleRG5BxSEztlwsJgb2CuX0YV0YOziqyUgHVxcLd12SSHFpNet35PHfd1Yy474JxxyFvGX3fgD6xYUcdb/DCT+wBoZmlomIiIi0vt0H1ivreZwlGEEzy0RERESkfTMMg2fmrCErvxxvT1fMJsjaX87j/1vJ8387BTdXS4vPuf5Asiwx/vDJr3NPjmPrnnzm/rYbDzcLOQUV+Hq5MqJfxAldy+F0ifAFIC27BMMwWn3mmoi0LSXLTsCH85Kw2gyG9A5j7KDow+5jMpnoFxfcuI5ERVUtSamF7M4oIju/gpAAT7pE+JIYH4qXx5GTXy4WMw9cPZy/vfAbWfvLmfX1Fu66NPGo8a3fUf/hMahXy5NlYUEHkmWaWSYiIiLS6hpmlp1IsqxhzYWcggpq66y4urS8s0FERERExF7WJuWyZXc+7m4WnrtrHB5uFv72/G+kZpfy6c87uPKsvi06X0l5DTsPlDxM7B122H3GDIhkYM8QNu3az/s/bAdg4siueLi1fjd4TJgPZrOJ8qo68ourCAnwbPXnEJG2ozXLjlNxWTVLNuwD4IpJfZp9nJeHK0N6h/HX0+K54+LBXDaxNycNjDpqouzgY+++dAgAP69OY0da4RH3zSusJD2nDLMJBvdq+TTjxjXLCitbfKyIiIiIHFlpRQ05B2bvn0gZxiA/DzzdLdhsBln7y1srPBERERGRVvHFr/UVuc4a3Y3oUB+C/T25+cKBAHyzZDcl5TUtOt/GHXkYRv2MriMlpkwmE3ddmtjYzh4cH8rFp8efwFUcmauLhejQ+nKSqdkqxSjS0SlZdpx+W59BndUgLtq/cW2xttC3exAThsUC8NbczRiGcdj91iXnANCrSyA+Xm4tfp6GmWU5KsMoIiIi0qp2H5hVFhHsdVzttAYmk4nosPrSL1q3TERERETak4zcUrbszsdsgvPH9WjcPmZgJHFR/lRWW/l68e4WnXNNUn1/59A+4UfdLyzQi+fuOoXXHziNR28c3axJCserS4QfAKlZpXZ7DhFpG0qWHafF6+tnlZ02PLbNn3vq2X1xd7OQlFrIbwfi+LOG+IYnHP3D40ga1iwrKK6kzmo7vkBFRERE5BC7DqxX1uMESjA2iAnVumUiIiIi0v78sjodgCF9wpvMAjOZTFw6sTcA3y7Z0+zZZTabwboD65UNPUIJxoNZzCaiQ+vLJNpTQ3s8K1+VHkQ6OiXLjkNRaXVjCcSTBka1+fMH+3vy1wm9AJj1zRbKKpp+qOQVVrJ5934ATh1yfMm8AF933FzM2AzYX6RSjCIiIiKtpTXWK2sQE6ZkmYiIiIi0L1abwcI19cmy00d0OeTxUf0j6B7lR2V1Hd8sad7sspTMYopKq/Fws5AQF9Sq8Z6IiOD6MozZKosu0uEpWXYc1mzPxjDq15gI9nfMwo0Xju9JdKgPRaXVvPv9tiaPfb90D4YB/XsEE36gnGJLmUwmQhvXLVMpRhEREZHWsrsxWXb865U1iD6QLNunZJmIiIiItBPrk3MpKKnC18uNEQkRhzxuMpm45Iw/ZpeVVdYe85wNs8oG9gzF1cXSugGfgIjg+r5XzSwT6fiULDsOa5Pq35yH9z30zb6tuLpYuO2vgwCYtyKVdQdiKiqt5odlewGYclA94OMRdqAUY67WLRMRERFpFWUVNWTn17etWqUM44E1yzLyyo64lq2IiIiISFv69cCssvFDY3B1OXz38+j+kXSJ8KWiqo7vft9zzHM29McO7XvsEoxtKTKkfmZZXpGWshHp6JQsayGbzWgscTg4PtShsQzoEcKk0d0AeOr91XyzeDeP/W8FldV1xEX5M/wwIzdaIuzArLScApVhFBEREWkNuw+sVxYe5IWvl9sJny8yxBuTCcoraykua956DyIiIiIi9lJntbE2KQeAkwdHH3E/s9nEJafHA/D1b7upqDry7LLSihq27y0AYEgz1itrS4G+HvVL2dgM8grVhyrSkSlZ1kJpOaUUl9Xg7mYhvkugo8Nh2pT+DOwZQmV1HW99vYUdaUV4urtw75VDT3gBy4YSjirDKCIiItI6WnO9MgB3V0tjNYCM3NJWOaeIiIiIyPHanlJAeVUd/j5u9DpG3+lJg6KJDvWhrLKW75emHHG/JRv2YbMZdI/ya1wjrL0wm02EH4hJpRhFOjYly1po0648APp1Dz7iNOK25Opi4V83jGLKKT3oHuXHSYOimH7HycSG+57wuUMDlSwTERGRzmPN9hwenrmUaU/+zHMfrCXHAaWmG5JlPVphvbIGMQfWLcvQumUiIiIi4mCrt9fPKhvaJxzLMQbyW8wmLj4wu+yrRbspLK067H4LV9eXdZwwrEsrRtp6Ig8ky3KULBPp0FwcHUBHsz2lfspvv7hgB0fyBzdXC9ef17/VzxuuNctERESkk/h68W7e/npL4/+z9pezj3be7gAAxlhJREFULjmXx24aQ1x06yWujqWhDGNrzSwDiA7zYW1SLvvylCwTEREREcdavS0bgGF9w5u1/ymJ0Xz5605Ss0t58aP1/OuGUU2qZW1LySc5rRAXi4lThhy5rKMjhQV6ApCrMowiHZrjp0Z1MMlphQD06eb4Eoz2FhZU/0a/v7gKqxaoFBERkQ5q0dr0xkTZpNHd+Of1I+kR409JeQ2PzVpBcVl1m8RRVlnbWJqlRysmy2LC6isKaGaZiIiIiDhS1v5yMnLLsJhNJDZzbTGLxcx9Vw3DzcXMuuRcPlu4o/ExwzD44KckAE4b3oVAXw+7xH2iGqpzac0ykY5NybIWyC+uJK+wErOpdUcDt1eBvh64WOoXqMwvPvw0aBEREZH2LLeggte+2AjABaf25La/DPp/9u47TK6CbP/490zZ3nsv2WQ3vVcCBEKTIiiCqKBiwQrvy4sNfxawIDYERUGxAYKKICi9hBpICCmkl0229977lN8fM7MhpOxuMrtnZvf+XBfXBTszZ57dhN2z5z7P87B8dhq3fWk1mclRNHf0c98TuyaklhLvCMaUhAhiIkP8dtysZN8YRu0sExERERHzbN3vGcE4Oz+RqHD7qF+XmxbDdR+aB8BDz+3nT//dzZDDySPritl5qBm7zcIVa2eMS83+kDzcWabpXCLBTGMYx6DY21WWkxZDRNjov+EHK4vFIDk+nLrmHhraeklJiDC7pONqbm7m9ttv580338ThcLBmzRpuvvlmUlKOfxdLUVHRcR9bvnw5f/vb38ajVBEREZkgbreb3z66nb4BJ7PyErj24tnDj0WG2/nGNUu46a7XeWN7DR9Ylce86UnjWo8vLJvux31lcHhnWWNrL4NDTkLsVr8e3x9O5lwNoKGhgZ///Oe8+eabDA0NMX/+fL75zW8ye/bsE75ORERERCbe7tIWABYWJo/5tReszKWje4CHnt/Pf98o4b9vlAw/du0ls0nz7gXzJ3+do04vnEV/1Gqa2g53vg0ODvLb3/6WJ598ktbWVvLy8vjSl77ERRdd5PfPQ0T8Q2HZGPh2TMzIjjO3kAmUGh9BXXOPZ29ZgdnVHJvD4eC6666ju7ubW2+9FYfDwR133MHnPvc5Hn/8cez2YwebjzzyyFEfe/HFF/nzn//Mxz/+8fEuW0RERMbZy5srebe4CbvNwv9ctfCI3QfgGYX4gVV5PLuhnD88sZO7bjoLm3X8Bi+Mx74ygLjoUCLDbPT0O6hr7iE3Pcavxz9VJ3uu1t3dzdVXX01ISAg/+MEPCA0N5Z577uEzn/kMTz311IgXMURERERk4rjdbvaVecKyOdMSx/x6wzC46rwi0pMiufffO+nuGyIyzMbVH5jFJafn+7tcv56j/ubu31L99h8JCbsJh9OFzWrh61//Om+99RZf+9rXyMvL47///S833XQTUVFRnHnmmX7/fETk1CksG4PSWs8FjvyMiVsCbzZfN1kgL6h8/vnn2bt3L8888wzTp08HYNasWVxyySU899xzXHrppcd83cKFC4/477q6Oh599FGuvvpq3eUhIiIS5Fo6+ob3lF19wczhvV7vd82Fs1i/vZaK+i6e3VDGpWeM391BB6vaAf/uKwPPhYXMlCiKK9upbuoOuLDsZM/VHnjgAdrb23n22WeHg7G5c+dy+eWX884773DJJZdM2OcgIiIiIifW0NpLa+cANqvllBoNzlyUxWnzM2hs9Uy5Gq+b2fx5jjp79hzWnn8x3c0ltHT0U1W6lxdeeIH77ruPNWvWALBq1SoqKip44403FJaJBCjtLBuDstpOAKZlTo6wbO3atfz2t7/lJz/5CStWrGDRokV87Wtfo6enh/vuu48zzzyTP972GWq3PEhldcPw6x599FEuvvhi5s6dy1lnncXdd9+N0+k84tiPPvool19+OQsXLmT+/PlcdtllPPfcc8OPP/7448yePZsdO3Zw1VVXMW/ePM4++2z+/Oc/H/GcoqKi4/5z9913A/Dmm2+Sn58//IMNYPr06RQUFPD666+P+uvx05/+lNDQUG666aYxfy1FREQkcLjdbu799056+h1Mz47jQ2uOH4BFR4TwqYtmAfD3Fw7Q0T0wLjV19gxS19IDQOEoLx6M5lxtyZIl3HDDDSR5JjFS3dg1ac7VXnjhBS644IIjOsiSk5NZv369gjIRERERkxzvHHXbvhpaD71K6bofs2rlcm644Qba2tqGXzeWc9SlSxbzgXNO4yOXfzgozlFTU1NY/bHbiclcRGNbL88//zw5OTnDQRl4bnD75z//yXe/+92T+KqLyERQZ9kodfUO0tzu6a7KC7C7dU/FX/7yF1avXs2dd97J7t27ueOOO9izZw8pKSn86Ec/4pWNu/jn/b/j9ef+zrc+eyZ/+MMfuPPOO7nmmmv49re/zb59+7j77rupq6vjJz/5CQAPP/wwP/7xj7nhhhtYsmQJHR0d/PGPf+TrX/86ixYtIi0tDQCXy8WNN97Itddey4033shjjz3Gz3/+cwoLCznjjDM466yzjjkq0cd3nJKSEvLy8o56PCcnh7KyslF9HbZv387zzz/P7bffTlRU1Bi/iiIiIhJI3t5dx6Y99disBv971SKsI9yNet6KXJ7bWE5pTQd/e24f11+50O81HazyXCjITI4kKiJk1K8b6Vyturqa2267jSX9Nog5i6f+/TBbXv1X0J+rDQ0NUVJSwqWXXspdd93FY489RltbG4sXL+b73/8+M2YE7oJ3ERERkcnuWOeob23aRr8rnIuv+ipzsqzcdtttJCUlccstt0ya64knOkeNLfogEEpLRz/79+9nxowZPPXUU9xzzz1UVFSQm5vL1772Nc4999xT++KLyLhRWDZK5d6uspSECCLDjz2zNhhFRUVx5513YrPZOO2003jiiSdoaGjg0UcfJTo6mqTsuTz1zDrqq4rp6urinnvu4aqrrhq+C+L0008nLi6O7373u3zmM59hxowZVFVV8bnPfY6vfOUrw++TmZnJ5ZdfztatW7n44osBz13fX/nKV7jyyisBWLJkCS+99BKvvfYaZ5xxBgkJCSQkJIz4OXR1dZGbm3vUxyMjI+np6RnV1+FPf/oTmZmZx22xFhERkeDgcLq4/+m9AHz4rOmjusnJajH4wofmcfPv3uTFTRWcszSHWfkjn4OMRXFlOwAzcuLH9LqRztUA1q9fz6HSA4TMXMHWNx6fFOdqnZ2dOBwO7r//frKzs/nxj3/M4OAgv/nNb7jmmmt48sknSU1NHdPXUkRERET841jnqJVVteSu/TYXnHc6axZnsX79erZt2zapriee6Bx1x2M/I3P1/9La0U9rayvl5eXs2bOH//u//yM5OZm///3vXH/99cMTIkQk8CgsG6Uy376ySdRVBjB//nxstsN/DZKSkoiIiBi++JKaEIE1JIK+rnq2bnuX/v5+1q5di8PhGH7N2rVrAXjrrbeYMWMGN998M+D5AVJaWkpFRQWbNm0CYHBw8Ij3X7Ro0fC/h4SEkJCQQG9vL+D54ff+duz3slgsWCwW3G73cZ9jGMaIX4P6+npefvllbr755iO+FiIiIhJ8Xni7gtrmHmKjQrhi7ei7j+ZMS+ScZdm8vLmKO/+xjV9/7SzCQ/13XlBc6eksK8weW1g20rkaQFxcHIMD+3G1VeJyDE2Kc7WhoaHhf//Tn/5EZGQk4NlZdv755/Pwww9rdLaIiIiISd5/jpqQmEht6yBWezgzcuIAzzlqcXEx7747ea4nnugc9dxzz6O9fAOtnYsZGhqiqamJxx9/nDlz5gCwcuVKLrvsMu655x6FZSIBSsnAKPn2leVnTI59ZT7HGjkYEREx/O/xMWEYBriBmtpGAL7whS8c81iNjZ7HKysr+f73v8/GjRux2+1MmzaNmTNnAhz1gygsLOyI/37vD6snnniCb3/728et/frrr+eGG24gKirqmHd8dHd3H3Eh6XhefPFFDMMYvkNFREREglNv/xD/eHE/AB8/fyYRYWObBnDdZfPYcbCZupYe/vzkbr56xYJR3XgzErfbPTyGsdB78WC0RjpX87FaDFxDnvOhyXCu5rvwsGLFiuF/B8jIyKCgoIC9e/ce931FREREZHy9/xx1YNCJYQkhKtxOemLkEY+1t7cDk/8cNSU9h46OWto6+4mMjCQ5OXk4KAOwWq2sWrXqhCMiRcRcCstGqazO21mWMbk6y0ZitRiEhdjoARyGZ7/GL3/5y2PO9E1KSsLlcvGFL3wBu93OY489xqxZs7DZbBw6dIj//ve/Y3rvs88+m8cee+y4j/sWaebn57Nv376jHq+srGT+/Pkjvs9rr73G0qVLSUpKGlN9IiIiElgef+0QHd2DZCRFcsHKo0eqjCQy3M6NVy3iu3/YwAtvVxAVbueTF83Gajm1wKyxrY+O7kFsVmPcbrwyDIOEhHjqgP/5xvc5c8XR50DBdK4WHR1NQkLCUXcRAzgcjqMukIiIiIiIeXr7PR1j07PjjrrZLCbGcy11MlxPPNE5qoETizWCls5+cnNzqaurw+12H/H10HmsSGA78bZzATy7LyrquoDJ11k2GmEhnkw1PnUadrudhoYG5s2bN/yPzWbjV7/6FdXV1bS1tVFWVsYVV1wx/BjAG2+8AXiWcI5WfHz8Ee/z/n98eypOP/10SkpKOHTo0PBrDx06RElJCatXrz7he7jdbnbu3MnixYvH9DURERGRwNLS0cd/Xi8B4NMXz8ZmPbnT3AWFyXz+srkA/PvVQ9z4q9fYsLP2hGNaRuIbwZiXEUuI3XrSxxlJ0ay5GBYrZRU1k+Jcbc2aNWzYsIHW1tbhj5WWllJWVsbSpUvH9LURERERkfHTN+AZTzgjO+6oxxYsWDCprice7xy1vraa8IQ8Wjv7WbNmDe3t7bz11lvDzxkcHGT9+vUsWbJk1J+LiEwsdZaNQk1jNw6ni/BQG6kJR4+9mezCQz0Xdfocdj7/+c/z61//mu7ublasWEFDQwO//vWvMQyDmTNnEh0dTWZmJg8//DBpaWnExMSwfv16HnzwQc8x+vr8Xt9FF13E73//e6677jq+9rWvAXDHHXdQWFjIhRdeOPy8vXv3EhISwvTp04c/VltbS1dX1xEfExERkeDzjxcPMDDoZFZeAqvmpZ/SsS47s4DYyBDufXwn5XWd3P7AZqZnxfLJi2azuChlzMc7UOEJy4518cCfCnLTiC84i2cff5CsxJCgP1f76le/yrp16/jc5z7HV7/6VQYHB7nrrrtIS0vjiiuu8HudIiIiInJy+gY8nWXHOt+Nj4+fVNcTj3eOmpKaSlTOclo7+7nkkkt46KGH+PrXv87XvvY1UlNTefDBB6mvr+fXv/613z8XEfEPdZaNQlmtZwRjXnoMllMcwxOMwrzL7Rtae7nxxhu5+eabeemll7juuuv4xS9+wZIlS3jooYeG5/nec889pKamcvPNN3PjjTeyY8cO7r33XqZNm8aWLVv8Xl9ISAh//etfmTNnDt/73vf44Q9/yMKFC/nzn/98xLLR66+/nh/84AdHvLalpQU43BIuIiIiwaehtZeX3qkE4NpLZvtlz9hZS7L54/87j4+eW0h4qJVD1R3cct9G/vLUnjF3me0qaQZgTn7iKdd1Ilkp0SQVXcDCNR+bFOdq2dnZ/POf/yQ1NZVvfOMbfP/732fmzJn8/e9/P+YuNxERERGZeP2DDvoHnQDMyI4/5nMm0/XE452jPvjg37DYwhgYdDLkNPjrX//KBRdcwJ133skNN9xAT08P999//xF7zEQksBjuU5kpM0X89ak9PP7aIS46LY8vf2SB2eVMuFe2VHLnP95lwYwkfvylE481FBEREZlo9/57B89uKGdhYTI/+uJpfj9+R/cA/3zxAE+/VQbAJy+cxUfPLRzVa7t7B/nE95/D7YYHbrmAhJjx21Gwp7SFm3/3Jinx4fz5u+eP2/uIiIiIiPgcqGjl679ZT1xUKA/eeoFfblwLVh/77rP09A1xzzfXkp0abXY5IjJG6iwbBV9n2VTcVwaQEu8ZPdnY5v+WZxEREZFT0dbZP9xV9tFzRhdgjVVsVChfvHw+X/6IZ9H3Q8/vY29Zy6heu6e0BbcbMpOjxjUoA8hK8XRbNbX30T/oGNf3EhEREREBqKzvAiA3PXpKB2XA8Pl+a0e/yZWIyMlQWDYKZXWdAORnTM1RfSnePW1Nbb24XGpEFBERkcDx5PpShhwuinLjmVswvmMOLzotn7VLs3G74TePbMfhHHnR+K4ST6g2b3rSuNYGEBMZQlS4Hbcb6pp7xv39REREREQqGzxhWU7a1Lxu+l6J3rCspVNhmUgwUlg2grbOftq7BjAMyJ2i3/QTY8KwWgwcTjdtXfpmLyIiIoFhyOHkxU0VAHzk7BkTcifrdR+aR1xUKDVN3by8uWrE5/v2lc0b5yAPwDCM4e6yKu9Fi0BR39JDaU0HQw6n2aWIiIiIiB/5Oss0dhASYr2dZQrLRIKSwrIRlNV6usoykiIJC7WN8OzJyWq1kBgXDkBDa6/J1YiIiIh4vL27ns6eQRJiwlg+O3VC3jMq3M4V58wA4J8vHThh+NPVOzg8zntewfh3lsHhO3or6gMjLOvqHeSHf36b636yjv/91Wt8/raX2Lir1uyyRERERMRPKus9105zFJYRHx0KKCwTCVYKy0Yw1feV+aR5RzHWt5g/0mfI4WJPacvwn42IiIhMTS9v9uwqO3d5DlbrxJ3WXrgqj8TYMJrb+3jh7YrjPm93STNut2eXWPw47yvzyU33XKSo8I4RN1P/oIPv3PsWm/c2YBgQHmqltXOAnz24hXcPNJpdnoiIiIicop6+IZq9+7ly0xSWDXeWaWeZSFBSWDYCX2fZVA/LMpI9I31qmswNy+pbevjfX73Kzb97k/+54zXu/Mc2nNqjJiIiMuW0dfXzbnETAGuXZk/oe4fYrVx1biEA/1pXTP+g45jPe3t3PQCLi1ImrLa8dE9nWXkAhGV/eWoPZbWdxEWF8uubzuLhH17EmQszcbrc/Orv22jvGjC7RBERERE5BVWNnmkGCTGhREWEmFyN+RJjPJO51FkmEpwUlo2grM7XWTY195X5ZA6HZd2m1eB0urjtr+9Q1dCNxbuS5JUtVTzy0gHTahIRERFzrN9eg8vlpjAnbvg8ZSKduzyXlIQI2roGePat8qMedzhdbNrjCctOm58xYXX5duw2tPbSN3DsEG8iHKpq5/mN5QB87erF5GfEYrdZ+N+PLSI3LZr27gH+9tw+0+oTERERkVPn21eWkzq1r5v6JHinSbQoLBMJSgrLTmBwyEl1oyccmuqdZZnJkQDUmhiWPbexnPK6TqIj7Pzle+fzfx9fBHju6DazLhEREZl4r22tBuCsxRPbVeZjt1n4+Hme7rInXjt0VHfZtv2N9PQNERcdysy8hAmrKzYqdHhXgm9/hBkeeGYvbjectTiLhYWHO+tC7Fa+esVCANZtrqS2WedwIiIiIsFqOCzTCEbg8BjGts5+3G5NwhIJNgrLTqCyoQuXy010hJ3E2InZMxGoMt8zhtFlwthDl8vNf14vAeDqC2aSGBvO2qU5LJmZgtPl5oFn9054TSIiImKO6sYuDla1Y7EYnLEw07Q6zlqSTWpCBO3dR3eXPbuhzPOcxVlYfS3xEyR3eBRj14S+r09xZRvbDzZhtRh88sJZRz0+Kz+BxTNTcLncPLW+1IQKRURERMQffDdnKSzzSIjx3LQ25HDR1TtkcjUiMlYKy06gvNY3gjEWw5jYixyBJjUhAqvFYHDISYsJSyp3HGyiobWXyDAb5yzPGf74Zy6Zg8WADTvr2FfWOuF1iYiIyMR7bZunq2xxUQpx3i4qM9isFj7m7S7750sHaOnoA6CqoYttBxoBuPC0vAmvy7e3rMKkzjLfDU5rFmeRkhBxzOdcdmYB4Bmp3W/iuEgREREROXmVDRrD+F52m5XoCDvg2bEsIsFFYdkJlNZ6LjDkTfF9ZQBWq4W0RM8oxpqmib9L2XdR7Kwl2YSF2IY/npsewznLPOHZX5/eoxZnERGRSc7tdr9nBGOWydXA2qU5FOXE0zfg4Pb7N9PRPcBfntqD2w0r5qSRkTTx+9R8e8sq6iY+LOvsGWTjrjoAPnjGtOM+b+GMZNITI+ntd7DB+3wRERERCR7dfUPDN9Rnq7NsWFz04VGMIhJcFJadQJm3s2zaFN9X5vPeUYwTyeVys22/5+7s0+anH/X41R+YSYjdyr7yVt7ZUz+htYmIiMjE2l/eRkNrL+GhVlbMTTO7HCwWgxs/voiocDsHKtu45pbn2bKvAYsBn7ro6BGEEyFveAxj54TfSPTatiocThfTMmKZnhV33OdZLAZrvGHnWztqJ6g6EREREfGXKu++ssTYMKLC7SZXEzh8oxhbOwdMrkRExkph2XG43W7KvJ1l+QrLAMhM8YRltU0Tu4j9UHU77d0DhIfamJWXeNTjibHhXOq9c/nB5/bhNGGnmoiIiEyMV7dVAbBqXsYR3eZmykqJ5gdfWEV2queO2shwO9/85DJy0syZTpCdFo3F8HR5tXVN3C/pbreblzZVAnDeipwRng2nL8gAYNuBRnr6tNNBREREJJhUNnj3laWqq+y94mPUWSYSrALjCkMAamjtpadvCJvVGL7wMdVlJnvGMFZPcFj2brGnq2xhYTJ227Hz3Y+cPZ3nNpZTWd/Fq1uqOHf5yBdoREREJLgMOVy8ub0GCIwRjO9VmBPPb79+Nm1d/URHhBBit5pWS6jdSmZKFFUN3ZTWdJDg/YV9vB2qbqe8rhO7zTKqP5+ctGiyUz11btpTz9ql2RNQpYiIiIj4w/C+MpNuEAtUCd4xjK3aWSYSdNRZdhylNZ4RjLnpMccNaKaajGRzOsv2lLQAMH960nGfExURwpVrZwDw8Av7GRxyTkhtIiIiMnG27W+gq3eI+OhQ5s9INruco1gsBomx4aYGZT4F3hGIB6vaJ+w9fV1lq+alExURMuLzDcNg9fxMQKMYRURERIJNpXcMo5oMjuTrLGvXGEaRoKMU6DhKarSv7P2yvGFZY2svQ46JCaOcThf7K1oBmDPt6BGM73XJGdNIjA2jub2Px145OBHliYiIyAR6dVs1AGcuysJqMUyuJrDN8IZlhyYoLOsfdPD6u54/n/OX5476de8dxdjbr1GMIiIiIsHCF5blpikse6/hnWXqLBMJOgrLjsPXWVZwgsXkU01cdCiR4XZcbqhqmJjustLaDvoGnESG2UZs6w61W/nsB+cA8K91xcN/hiIiIhL8unsH2bynHoCzlgTWCMZAND07DvCMRpwIG3bW0dvvIDUhgnknmAbwfjlp0aQnReJwuthxsHkcKxQRERERf+nuG6LVu5NLnWVHio/WzjKRYKWw7DhKvBcWCjLVWeZjGMZwp11pTfuEvOeeUk9X2az8xFHdQX7GwkxWzUvH6XJz1z+3MaBxjCIiIpPCy1uqGHS4yEuP0fnZKEzLiMViMWjt7KeprW9Ur3G73Ryqaue1bdXsKW3B7XaP+v3WveMZwXju8hwsY+j6MwyDJTNTANi6v2HUrxMRERER81TWdwKQFBtGZLjd5GoCS7yvs0xjGEWCjsKyY2jr7KetawDDgLx0Lal8r2nei1MlE9S1tbfMs69spBGMPoZh8OWPzCc6IoSy2k7ueHgrTtfoL/SIiIhI4HG53Dy3oQyAi07LwzA0gnEkYaG24fM23/nUiQw5XPzq79v4v7te546Ht3Lz797k14+8i9PpGvG1tc3d7CppxjDgnKU5Y651ycxUwDOKcSwBnYiIiIiYwzeCcaQpUFNRgndnWd+Ag/4Bh8nViMhYKCw7Bl8QlJUSRViozeRqAstwWFY9/mGZ2+1mT6k3LMsfXVgGnnbnb1+7DJvVwsZdddzz2A5cCsxERESC1qY99dQ09RAZZmPNYo1gHK3Z+QnA6MKyvz69h9e2VWMYh0c4vry5ij8/tWfE1z63oRzwhF7J8eFjrnNuQSJ2m4Wmtj6qGrrG/HoRERERmViVDb6wTCMY3y881EZoiBWAti51l4kEE4Vlx1DiHTE4LSPO1DoCUUGWJywrr+sY9wCqurGbzp5BQmyW4Ys2ozWvIImvX7MEw4AXN1Xwy4e3MuQY+c5oERERCSxut5vHXikG4KLV+USEaczLaPluNtpb1nrC5+0qaeap9aUA/L9rl3PnjWv41qeWAvDU+lK27W887msHhpy8vNkzgvHC0/JOqs6wEBtzvVMEth04/nuJiIiISGDwjWHM0b6yoxiGQYJ3b1mr9paJBBWFZcfg65qapn0YR8lKjiLEZqFvwEldS8+4vteBijYAZuTEY7eN/a/q6vkZfO0TS7BZDdZvr+GHf3qb3v4hf5cpIiIi42hXSTPFle2E2CxcekaB2eUEFd8Y6/K6zuP+ou5yufmLt3vsgpW5rJybDsDpCzK59IxpANz3n50MOY69B/atHTV09Q6REh8+PE7xZCyZ5Xnt1n0Ky0REREQC3eExjArLjiUu2rO3rK1LYZlIMFFY9j5ut5sDFZ67b4ty402uJvBYrRbyMjzziEuq28f1vYorPWFZUc7J/zmsWZzF9z63krAQK9sPNvGT+99Rh5mIiEiQcLrc/O3ZfQCctyJ3+JdOGZ3YqFBmeLvzt+xrOOZz3tpRy6GqdsJDrVz9gZlHPPaJC2YSFx1KTVMP/3m95KjXut1unn2rHIALVuZhtZz8LrnFRSkA7C5t0W4HERERkQDW2TM4PF4wW51lx+TbW6bOMpHgorDsfZrb+2ntHMBiMYZHDsqRCjLjACitGd+9ZcVVnrCs8BTCMvBcfLnty6sJD7Wy42Az9z8z8u4NERERMd/fX9jP/oo2wkNtfOTsGWaXE5SWeTu2Nu+tP+qxIYeLB5/bC8CHz5pBvHdcjE9kuJ3PXDIHgEfWFdPY1nvE4zsONnGgsg2b1cJ5K3JOqc6slChSEiJwOF3sLGk+pWOJiIiIyPjxjWBMiQ/XiPTjiI/xdpZ1ameZSDBRWPY+Byo9XWX5GTGEhdhMriYw+cZTloxjWDYw5KS81vPDd0ZO3CkfrzAnnq9f7dm98eQbpezSRRgREZGA0t03RFVDF+V1newvb+Wef+/gX+s8u8q+dPl8kuPDTa4wOC2fkwbA1v2NdPcdOY76+Y3l1Lf0EhcdyofWHHvE5dlLspidn8DAoJPfP75zeGetw+ni/mc8QdtFp+UdFbSNlWEYLPF2l209TheciIiIiJivssE3gjHG5EoCl6+zTGMYRYKLwrL32V9+6qP/Jjtfx93BqvbhCyb+VlbTgdPlJi46lOQ4/1wcWz4njQtW5gJw77934HBqHKOIiIjZdpc0863frufj332Wr/z8FW745at84+71PLehHPCMAly7NNvcIoPYtMxYctOiGXK4WL+9ZvjjXb2D/OPFAwB84vwiwkOPfZOYYRh86fL52KwWNu9t4E9P7sbpdHH/03spqe4gMtzOFef4p+tvyUxPWPbugSa/HE9ERERE/K+iznNze672lR2X70YydZaJBBeFZe/j21c2My/B5EoCV35GLGEhVnr6hqjwtl77m29fWWF2PIZx8vsv3u/ai2cTGxVCVUM3L71T6bfjioiIyNi98W413/n9BvaWec6/IsPtxEWFkhQbxtJZqfzoi6v4+PlFJlcZ3AzD4JxlnhGJT60vxem9WeiBZ/bS1TtIdmo0563IPeEx8jNiueGjC4aP8eFvPcV/3/DsMPvy5fNPuavMZ970JKwWg7qWHupbevxyTBERERHxL3WWjcw3hlE7y0SCi+YMvseQwzk8WrAoV51lx2OzWpiVl8C7xU3sKmkmP8P/u92KK9sBKPTDCMb3iooI4aPnFvLH/+zmsVcOct7yHGxWZcYiIiITraqhi18/sh2Xy82ZCzP5zAfnkOSnbnI50nkrcnn05YNUNXTx+GuHSImP4IW3KwD4ykfmj+pcaO3SHCyGwT3/3knfgIPQECvXXTaPNYuz/FZnRJidmXkJ7Clt4d3iJi5cFem3Y4uIiIjIqXO73VTU+cIydZYdj8YwigQnpQTvUVbbyZDDRXRECOmJ+uX8ROZNTwJgd0nLuBx/uLNsHMZhnr8il9ioEBpbe3nj3Wq/H19ERERG9qcndzM45GRhYTJfu3qJgrJxFBVu55oLZwLw4LP7+OXDWwH40JoC5hYkjfo4Zy3J5sFbLuCX/3MGf7v1A8Pjrf1pUWEyAO8eaPT7sUVERETk1LR3D9DVO4hhQHaqwrLj8U1e6Oge1BoYkSCisOw9fCOAinL9O/pvMprvDct2HGzy+zf9ju4B6ryjd2Zkx/n12ABhITY+tGY6AP9adxDnOO1dExERkWMrrmxj2/5GLBaDr3xkARaLzrvG24Wr8vjYeUVYLQYWAy5Znc+nLpo95uOEhdooyk047o6zU7XQG5btPNg0PDJSRERERAJDpberLC0xklC71eRqAldMZAhW7+847V3aWyYSLAJ+DKPD6eKxVw4SEWbj3GU5RITZx+293i323ME6ryBx3N5jspieHU9MZAidPYPsK2sd7jTzB19XWVZKFFERIX477ntddFoej71ykJqmbnYcbGJxUcq4vI+IiIgc7Zm3ygBYsyiT9CR1808EwzC4+gMz+cja6bjdjFvYdaqmZ8cTGW6np2+Ig9XtzMzVHmERERGRQFHR0AlArkYwnpDFYhAXHUpLRz9tXf2aoiESJAK+s6y0poOHn9/PH/+zm2/f8xa9/UPj8j4DQ052H2oGYMnM1HF5j8nEajFYOsvzdXpnb71fj72/whOWjefeuIgwO2cv8ezYeNG7s0NERETGX9+Agw07awG4cFW+ydVMPWEhtoANysBzjrlwhm8UY5PJ1YiIiIjIe5XVeMOy9BiTKwl88dGhALR1qrNMJFgEfFg2IzuO669cQFS4ndKaDv785J5xeZ/dJc0MOlwkxYZpQeUorZybBsBrW6sZcjj9dtwDFb5xmON7J/H5Kzx7NjbtqaO7b3xCWBERETnSxl219A86SU+KZGbe+N0YI8FrUZH2lomIiIgEooNVnhvcZ2TFmVtIEIiP8ewta+3sN7kSERmtgA/LDMPggpV5fOczywFYt7mSmqZuv7/P1v2eX8aXzErVvrJRWjY7jYSYMNq7B9iws84vx3S63BRXtgMwcxw7ywDyM2LJTo3C4XSzZV/DuL6XiIiIeLyypQqAtUuzdc4lx7Sw0DMe+0BlGz26oUlEREQkIPQPOKhq8Owsm5Gjm95GkuANy9oUlokEjYAPy3zmFiSxbHYqLpebp9aX+v342/Z7whLtrho9m9XCB1blAfDshjK/HLOqoYu+AQdhIVZy0sa/pXvl3HQA3t7ln7BPREREjq+prY+d3rHXZy/JNrkaCVSpCRFkJEXicrmH/76IiIiIyKkpq+3gd4/t4I//3UVFXeeYX19S04HLDYmxYcNBkBxffLS3s6xLYxhFgkXQhGUAl6yeBsAb79Yw5HD57bj1LT3UNPVgtRgs8O5IkNE5f0UOVovB3rJWymo7Tvl4vhGMhTnxWC3jf7f5qnmesGzr/gYGhvw3SlJERESO9s7eetxumJ2fQGpChNnlSADz3cC2db+6/0VERERO1f6KVr5x93qe31jOk2+U8j93vMr6d2vGdIziSu8Ixuy4cahw8kmI8e0sU2eZSLAIqrBsQWEyCTFhdPUO+vUXZ98Ixpl5CUSG2/123KkgMTZ8OHC6/5m9uN3uUzre/nLPD96icR7B6DM9K46k2DD6B53sKNYSeRERkfG0zXvOtXRWqsmVSKBbNtuzG3fz3npcrlM7vxQRERGZypxOF797dAcDg04KsmJZVJiMyw2/+sdW9pe3jvo4e0pbAJiVlzBepU4qvp1lbV0Ky0SCRVCFZVaLwekLMwB4e7f/xub5grclMzWC8WRc/YGZ2KwWtu1v5PmN5ad0rH3lnh+8M3Mn5gevYRjDoxg3ahSjiIjIuBlyuNh5yHNjisZey0jmTU8kPNRKa+cAJTXtZpcjIiIiErTe3FFLeV0n0RF2fviF07jlulWsmpeOw+nmZw9upqN75DGBLpebvWWeYG32tMTxLnlSiI/2dJa1dp7cGMbu3kH+8eIB3tlT78+yROQEgiosA1g5xxNsvLOnAafz1EcxDjmcw7sQlszUXc4nIyslmk9cUATA75/YxZZ9J9f119TWR01TDxZjYn/wrpjruXN524GGU+6MExERkWMrrmyjf9BJXFQo+RmxZpcjAc5us7Kw0BOqvrNHoxhFRERETtarW6sAuGh1PjGRIVgtBjd+bBGZyVE0d/Tzy4e24hyhk7+6sYuu3kFC7FYKMuMmoOrg5+ssa+/qH/P1xr4BBzfe+Tp/f2E/t/1100lfaxWRsQm6sGx2fgLREXa6egc54J2Veyr2lLYwMOgkPjqU/IwYP1Q4NV2xdgZrl2bjcnnuStl1EsvYdxz03G0+PTuOqAkchzkrPxG7zUJr5wDVjd0T9r4iIiJTiW9sy5yCRCwTsJdUgt9y7yjGd/bqbloRERGRk9HeNcC73rUjZy/JHv54RJidb1+7jNAQK9sPNvGPF/ef8Di+Y8zKi8duC7rLyaaIj/aEZQ6nm86ewTG99uXNlTS09gLgcsN9T+zSaHKRCRB0392sVgvzpycDsKtk7IHM+/n2lS2emYJh6MLNyTIMg+uvXMjiohT6B53c+seNw3tJRssXli2YkTweJR5XqN06PG9550mEfCIiIjKy4bAsX2NbZHSWzkrFMKC0poPm9j6zyxEREREJOtuLG3G53EzLjCUzOeqIx3LTYrj+igUAPPJS8Qm7lzbt9ty85NsrKyOz2yxER4QAntBytNxuN0+/WQrAZy6ZTXiolbqWHvaUtYxLnSJyWNCFZQBzCzwXWfaUnPo3CV9YphGMp85us/Cdzyxn6axUBh0ufvSXTWwa5W45p9M1/EPZjD0m82ckAYcDOxEREfEfp9PFPu/ycN95nMhI4qJDKcqJB9RdJiIiInIydntvWJs/PemYj5+1JJsLT8sD4BcPbaGirvOo53T2DA4HNSvmKCwbi4QY396y/lG/pq65h5qmHmxWCxeels8ZC7MAeHVL1bjUKCKHBWVYNse7z2pfeesp7S1rbOulqqELiwELCye2m2myCrFb+X/XLue0+ek4nC5uf2Azb+2oHfF1e8pa6O4bIiYyZLjLayL5utl2HWpWW7OIiIifVTZ00TfgIDzURk6axl7L6C33XpDRYnMRERGRsdvtnco1d9rxb1i77rK5zJmWSG+/g1v/9DYtHUd29D+/sXy4Oy0tMXJc651sfKMY27pGH5b5JqkV5cYTHmrjtPnpR3xcRMZPUIZluWkxRIXb6R90UlLTcdLH8Y0JLMpNGG6LlVNnt1n45jVLWbMoC6fLzc8f2sKbO2pO+JqNOz0daMtmp2K1TvxfyxlZcYSH2ujuG6Ks9uT/TomIiMjRir17Zmdkx2HVvjIZA9/esp2HmukbcJhcjYiIiEjwaOvqp6apB8M43HhwLHable98ZjmZyVE0t/fxo79sord/CPB0lT25vgSAD60pmJC6J5P44c6y0Y9h3O2dpDavwNMNODM3AcOA+pbeMXWoicjYBWVYZrEYw9/kd5/CKMat+71j/2ZO/Ni/yc5qtfB/n1jMOcuycbnc3PHwtuFdJe835HDx+rueMO30BZkTWeYwq9Uy/Hdqx0HdqSEiIuJPxZXtgOfuSJGxyEmLJj0xkiGHi80axSgiIiIyaqXeBoOMpCiiRmgSiI4I4dbrVhIbFUJJdQffvHs9T79Zyq1/3EhH9yAZSZGcudCca3bBLCHG21k2hpDLNzrTN74+MtxOXrpnOse+slY/Vygi7xWUYRkcviNid+nJBRtDDtdwKLJEYdm4sFoMbvjoIlbN84xk/PFfNlHV0HXU897ZU09X7yAJMWEsMmFfmc8C794ytTWLiIj41+HOMoVlMjaGYXDGIs+FmTfePfGkAhERERE5zBeWFWTGjur5aYmR3PL5lcRFhVJR38UfntjFwap2wkOt3PzpZaZMggp28b6wrGt0nWXtXQM0t3vGYM7Ijhv+uG9lzf4KhWUi4ylov8v50vW9pS04T2LH1P7yVvoGHMRGhVCQGefn6sTHajG46ROLKcqNp7tviFv/9PYRc3qdLjf/eHE/AOcuzzF1NNNcb3vz3rKWU9qFJyIiIof1DTiorPcsCldnmZwM313MW/c30N07aHI1IiIiIsGhrNZzDp4/yrAMPDe33XXTGq48ZwZLZ6Vywcpc7vq/s8jPGP0x5LAE786y0Y5P9AWcmcmRRITZhz9ekBUHQLn3z1RExkfQhmXTMmIJC7HS0++guvHobqWR+EYwLipKwaLdGeMqLMTG9z67gvTESBpbe/nhnzfR3eeZffzYy8VU1HcRFW43ffZxfkYskWE2evsdlGpvmYiIiF8cqm7H5Yak2LDhMSQiY5GbHkNuWjQOp5uNu+rMLkdEREQkKPiCl2ljDLoSY8P51EWzueXzK7n+yoVkJEeNR3lTQpx3Z9loxzCW1LQDh8MxH98YxvJ6hWUi4ylowzKr1cJ0bzvqgYq2Mb9+24FGAJaYOPZvKomNCuXW61YSHRHCoap2bvjFK3zjN2/w0POerrJrL5lD9Ajzk8eb1WIwZ5p3FOOhk9+FJyIiIocd9I5gLFRXmZyCMxdlARrFKCIiIjIa/YMOapu7AcjPiDG5mqlreGdZ1yjDsmrf6My4Iz6ekxqNYXjGNLaPcqSjiIxd0IZlAEU5nosuvj0Yo9XW2T/cimzmjqypJiM5itu+fBoJMWE0d/Szv6INiwFXnVfIBStzzS4PgHnTPeM9tbdMRETEPw74wjLtK5NTcKZ3b9nOQ020dPSZXI2IiIhIYKtp7MbthugIO3HRoWaXM2XFe7/2fQNO+gYcIz6/zDvpalrmkQFnWKiNtIRIACrq1F0mMl5sZhdwKnx7L8baWbb9YBMABVmxxEbpB8ZEys+I5d5vrWXLvgb6B53Mn55EWmKk2WUNe//eMi0vFREROTUHq9oBKMxRWCYnLy0xkll5Cewrb2X99ho+tGa62SWJiIiIBKyqRk9XWVZKNIah9TNmiQizExZipX/QSVtXP+Ghxx9pOTjkpL6lB4CctKO7AXPTo6lr6aG8vpMFhcnjVrPIVBbUSYDvoktlfSe9/UOjft273hGMC2foG4sZIsLsnLkoi/NX5AZUUAbaWyYiIuJPXb2DNLV5uoCmjWGxuMixnLXEM4rx1S3VJlciIiIiEtiqG7oAyE6NNrkSifeNYuw88fjEmqZuXG6IDLcPd6S9l+/Psqap2/9FiggQ5GFZYmw4yfHhuNye5fGj4Xa72V7s6SzTCEZ5P6vFYPY0zyjGHQdPbhSjw+mivqUHl8vtz9JERESCjm+MSGpCBJHhdpOrkWB3+oJMbFaD0toOjZ8REREROYFqb2dZdurxO5lkYviCr9bOE+8tq/IGnJ79ZEd3A2Yme/4saxWWiYyboA7L4HB32WhHMVbUd9HWNUCI3crs/ITxLE2ClK/jcIc3VB2LV7ZU8albn+e6n6zjiz9dR8koQ1wREZHJqLTGE2ioq0z8ISYyhCUzUwF4dWuVydWIiIiIBK6qRk/wkpWizjKzHe4sO3FYVjlCN6AvLKtpVFgmMl6CPiybOca9Zb4RjPMKErHbrONWlwSvhd65v3vKWhgYco76dc9vLOfOf2yjq9czErS+pZdb//j2iHeOiIiITFa+zrL8DIVl4h9nL8kG4PVt1eriFxERETkGl8tNXbNn91VWijrLzJbgDctG21l2vLAswxuWNXf00z/g8GOFIuIT9GFZUY6nO+xAZRtu98i/MPtGMC4s1AhGObbs1GgSYsIYcrjYV9YyqteUVLfz+8d3AvDhs6bzt1s/QF56DO3dAzz03L7xLFdERCRgldZ4wrJpGUcvqBY5GctmpxIZZqO5o589paM7TxMRERGZStq6+hlyuLBYDJLjws0uZ8pLivX8GTS1953wee8dw3gsMZEhREd4RtvXtfT4sUIR8Qn6sGxaVixWi0F71wCNbSf+pjM45GR3iWcP1aKi5IkoT4KQYRjD3WXbRzGK0eVyc8+/d+B0uVk1L53PXDKbuOhQvvKRBQCs21xJbbNapEVEZGoZcjiHf+GblhlnbjEyaYTYraxekAloFKOIiIjIsdS39AKQEh+O1Rr0l36DXmpCBABNJ7huPeRwUdvkCcCO11kGh7vLarS3TGRcBP13zFC7lXzvHoziEUYx7i1rYdDhIiEm7LgpvQgcHsW4/eDIYdnG3XUUV7YTHmrjS5fPH17COSs/gcVFKbjd8OLbFeNar4iISKCprO/C6XITHWEnKS7M7HJkEjlrSRYAb+2sHdPIbBEREZGpoN7bdZSWEGlyJQKQHO/pLGto7T3uc+qau3G63ISHWk/4u1OmwjKRcRX0YRlAUY5nb9n+ytYTPm/rfs++soWFycOBhsixLJzhCctKazro6B447vPcbjf/fuUgAJeeMW14DrHPB1blAZ7uMofTNT7FioiIBKD37ivTeZf405z8RJLjw+ntd/DOnnqzyxEREREJKL7OstTECJMrEYCUeM+fg2885rFUNXjCr+zU6BP+7uQLy3xdaCLiX5MjLMv1hGX7yk4clm3Z1wDA0lmp416TBLf4mDDyM2Jwu2Hr/objPm93aQsHq9qx2yxccvq0ox5fPjuV2KgQOroH2VOivRoiIjJ1lPj2lXknAIj4i8VicNZiT3fZa1urTa5GREREJLDUt3o7yxLVWRYIYqNCCLFbcbuh+Th7yyq94+tPNIIR3tNZ1qjOMpHxMCnCsjnTEgHPRZne/qFjPqeuuYfqxm6sFoNFRSkTWZ4EqeWz0wB4Z8/xw7LHXz0EwLnLcoiLDj3qcavVMnycjbvrxqFKERGRwFRW2wl4OstE/M0Xlm3d33DCKQAiIiIiU02Dt7MsTZ1lAcEwDFK8oxgbjzOK0bfreaS1QRnJngC0uqkbt9vtxypFBCZJWJYSH0FaYgQul5u9x+ku27zPM6JlzrREosLtE1meBKnlczwh17YDDcfch3Goup0t+xqwGPChswqOe5zT5mcAsGl3nX6QiYjIlOByuSlVZ5mMo5y0GAqyYnG63Ly5vcbsckREREQChnaWBZ6UBE9w2dB24rBspM6y9CTPn2lP3xCdPYN+rFBEYJKEZQDzCpIA2HWo+ZiPb96rEYwyNtOz4kiJD6dvwMnbu47uCnvkpQMAnLkoi4ykqOMeZ/70JOw2C80d/VrAKSIiU0JjWy99Aw5sVgtZKcf/GSlyKs5anA3Aq9s0ilFEREQEoH/QQVuXp+tenWWBI80blvmCzPdyOl1Ue8cq5qTFnPA4YSE2kuI8XWq6xijif5MmLJs/IxmAbQcaj3qst3+I3SWeEG3ZbIVlMjoWi8E5y3IAeOmdiiMeK6vt4O3d9RgGfPTcwhMeJ8RuZVZeAgA7jxPmioiITCa+rrLc9Ghs1klzuikBZs2iTCwGHKhoo9bEiwVb9jVwx9+3su6dSlwuTREQERER8zR4x/xFhtuJiggxuRrx8e0aqz7GrrH61l4cThehIVaSvUHYiWR4u8uOFbyJyKmZNFcvFhelYBhQXtd51LLErfsbcTjdpCdGDn9zEhmNc5blYDFgx8FmDlW3D3/84ef3A3DGgswRW6QB5s/wdD7uONg0LnWKiIgEktJa7whG7SuTcRQfE8bCQs8u4tdM6i57dWsVP/jT27y2tZpfP/Iu9z+z15Q6RERERED7ygJVpnfaxrG6wSrrvSMYU6KwWIwRj+UbxVjbrLBMxN8mTVgWExlCUU48AJv3NRzx2KtbqwA4fWEGhjHyNx0Rn9SECM70LpC//+k9OF1uNu2uY9OeeiwWg4+dXzSq4/jGhO4ta9XeMhERmfTKajoByFdYJuPs7CWe87TXtlZP+DlWT98Qf/rvbgCSvUvbn3jtEPvLj71DWURERGS8aV9ZYPI1b9Q19+B83ySCynrP705Zo7gZHw53ltUpLBPxu0kTlgGsmJsOwOvvubO0vWuAbfs9oxnPXpJtSl0S3D52XhEhNgs7DjZz469e4+d/2wLApWdMG1VXGUBBVhwWi0F71wDN7f3jWa6IiIjphjvLMhWWyfhaOTedsBArdS09HKhom9D3fuatMjp7BslMjuK+b5/L2qWe3zX+80bJhNYhIiIi4lPfqs6yQJQcH4HdZmHI4aKprfeIx0pqxjaVI11hmci4mVRh2dlLsrAYsKe0hdpmT1vrM2+V4XS5KcqJH3WwIfJemclR3PjxxVi8Yz4HHS4WF6VwzYWzRn2MULuVPO+SzuKqib2QIyIiMpE6ewaHR2LnpZ94QbXIqQoLtbFynueGOd80iYngdrt5ZUslAFesnYHNauHDZ00HYOPOWtq6dHOUiIiITDzfGMbUBIVlgcRqMYZDrvePYvSFZQVZow3LDnepiYh/TaqwLDE2nIVFnr0F/3zxAJ09gzzzVhkAHzqrwMzSJMidsTCT33ztbK46r5CbPrGY731uBaF265iOMSMnDoCDlQrLRERk8irzdpWlJUYQGW43uRqZCnzTI9Zvr2HI4ZqQ9zxY1U5NUw8hdiunzfeEdXnpMUzPisXlhnf2NIxwBBERERH/a2r3hGXJ8QrLAk2Ot4mjvLZz+GPdvYM0ersBp2XGjeo4ad4gtLtviK7eQf8WKTLFTaqwDODqC2ZiGPDq1mqu/v5zdPUOkpUSxSrviEaRk5WbHsM1H5jF2UuysVnH/r/OjOw4wHNxRUREZLIq0whGmWALpicRFxVKV+8Qu0uaJ+Q9395dB8CKOWlEhB0OhVd6f+fYtKduQuoQERERea+mNs+EB98+VQkcBVlxwOFOsvf+e2pCBFGjvNEwLNRGQkwYoO4yEX+bdGFZYU48l3tHoACE2Cx845qlWE8i3BDxp8KceAAOVbfjck3sAnoREZGJUjrGmfsip8pqtbB8ThpwOMQab1u9O5GXzko94uO+Hco7ipsYcjgnpBYRERERgL4BB919QwAkxyksCzQF3psJS6rbhz+2v6IVgOneG+xHyzfSsVZhmYhfTcoE6dMXz+bGjy3iQ2sKuOums3RnswSEnNRoQuxWevsdwzv1REREJhtfWJav8y+ZQKu8e8ve3l0/7jcltXX2D/89X+wdAe+TmxZNXFQogw4XxZXt41qHiIiIyHv59gZHhtmO6HyXwODrLKtt7qG33xNq7j7UAsC8gqQxHSvDG5aps0zEvyZlWGYYBucsy+Fzl84l2zsPVsRsVqtl+C4SXTwREZHJaHDISVWj54YQdZbJRJo/PYnwUCutnf0ces/duuNhxyHPqMeCrFjiokOPeMwwDOZMSwRgT2nLuNYhIiIi8l6HRzBqX1kgiokMIcU7HnN/eRtDDhd7yz2dZXMLEsd0rPThsEw344v406QMy0QC1YycOAAOVrWZW4iIiMg4qKzvwuVyEx0RQmJsmNnlyBQSYreyZKZnJOLGXeM7inFfmScE84Vi7+f7+ETtTxMREREBaPJ2liVpBGPAWuSdSvD2njr2lrUwOOQkJjKEnDE2e6Srs0xkXCgsE5lAvs6yiroukysRERHxP9+C6vyMGAzDMLkamWpWzvWNYhzfsGxvmecO4Nn5Jw7LDlS2aU+tiIiITJim9l5A+8oCme98ddPuOp7fWA54xomP9Xen9ERvWNaisEzEnxSWiUygnLQYAMrrOnG7dfFEREQml9KaduDwPH6RibR0Vio2q0F1YzdVDeNzY1JP3xAV9Z0AzM5LOOZzctOiCQ3x7KmtadJoHBEREZkYzeosC3gLZiQRGWajtXOAN3fUAnDhqrwxH8fXWdbRPUhP35A/SxSZ0hSWiUyg7NRoDAO6egdp7x4wuxwRERG/8nWW+TqpRSZSZLid+dOTgfHrLjtQ0Ybb7bmbNz7m2KNGrVYL072B8YEKjd4WERGRiXF4Z5nCskBlt1n5/GXzhv971bz0k7rRMCLMTlyUZ3euustE/EdhmcgECrVbh1ulK+o6Ta5GRETEf5wuN2W1np9tBVkKy8QcK+eN7yjGvd59ZbPyj91V5jMjOw6AYu2pFRERkQni21mmMYyB7dzlOfzfxxdxw0cX8q1PLTvp42hvmYj/KSwTmWC56Z5RjBX12lsmIiKTR01jF4NDTsJCrGQkRZldjkxRK+akYRhQXNlOS0ef34+/r9yzr2zWcUYw+hTmxANwsKrd7zWIiIiIvJ/b7dYYxiCydmkO56/IxWo5+T3PCstE/E9hmcgEy0mLBtRZJiIik4tvBGN+RiyWU/ilT+RUJMSEUeQNqt7eXe/XYzucLvZ7xyrOHqGzbJp3FGllfRdOl/bUioiIyPjq6B5kyOHCMCAxVmHZVKCwTMT/FJaJTLA8b2dZpTrLRERkEin17SvTCEYx2apxGsVYWtPB4JCTqHA7WSnRJ3xuWmIkIXYrg0NO6rVHQkRERMaZr6ssPjoUu02Xe6cC35oX7SwT8R999xSZYLlp3rCsoROX7jQWEZFJoqTaG5ZlKiwTc62c6wnLdh1qprt30G/H3VvmHcGYnzBi96TVYgxPEyiv1TQBERERGV9N7b0AJMdFmFyJTBRfZ1ltU7fJlYhMHgrLRCZYelIkNquFvgHn8PJVERGRYOZ2uymtaQegICvO1FpEMpKjyEmLxulys3lfg9+Ou6+8BRh5X5lPvneaQFldh99qEBERETkW3/WlpHiNYJwqslI8e6Lbugbo7hsyuRqRyUFhmcgEs1ktwz/QKup1p7GIiAS/htZeevod2KwWslNPPJ5OZCKs8naXvbWj1i/Hc7vd7PN2ls3OTxzVa3yjt9VZJiIiIuOtqc0TliXHKSybKiLC7CTFhgFQpVUvIn6hsEzEBL6xPBV1ungiIiLBzzeCMS89GptVp5divtMXZgKwdX8jPX6407a+pZe2rgFsVgszsuNG9Zq8DE9YppujREREZLz5OssUlk0tvhsVKxsUlon4g65miJggx/vDrLpRc4VFRCT4lWgEowSY3LRoslOjcThdvL277pSP5xvBOD0rlhC7dZQ1eMKy+pZeevs1GkdERETGT7NvDKPCsiklx3u+Wdmgm7NE/EFhmYgJfHd+VOnODxERmQRKajydZdMyY02uRMTDMAzO8HaXrd9ec8rH2zvGEYwAsVGhJMR4RuNUajSOiIiIjKPhMYzaWTal+CZX6VxTxD8UlomYIHu4s6wLt9ttcjUiIiInz+12U+odw1igsEwCyBkLMwDYXtxEZ8/gKR1rb5mns2xWfsKYXucbxVim0dsiIiIyThxOF21d/QAkx0WYXI1MpBzdjC/iVwrLREyQnhSJ1WLQN+Ckub3f7HJEREROWlN7H+3dA1gsBrnpMWaXIzIsKyWaaZmxOF3uU+oua+vsp6qhG8OAOdNG31kGkOcdjaM9tSIiIjJeWjr6cbvBbrMQGxVidjkygXw347d09NPthz29IlOdwjIRE9isFjKSIwHd/SEiIsGtuLINgPyMGMJCbCZXI3Kkc5ZlA/Di2xUn3c2/q6QZgPz0WKIjxnYBKjs1CvBMExAREREZD+/dV2YYhsnVyESKDLeTGOsZ+12t64sip0xhmYhJfHd/VOqHmYiIBLEDFZ6wrDAn3uRKRI529pJs7DYLpbUdHKpuP6lj7DzkCcvmz0ga82uzhkfjdJ/Ue4uIiIiMpKmtF4DkOO0rm4p8oxgrtLdM5JQpLBMxSXbK4b1lIiIiwcrXWVaksEwCUHRECKvne3aXvfB2xUkdwxeWzZs+9rDMd77X2tlPj0bjiIiIyDhobDvcWSZTT3aa72Z8jf0WOVUKy0RMMtxZpjs/REQkSDmcLg5VtQPqLJPAdf7KXADeeLea3v6xBVZNbX3UNfdgMWBO/tj2lYFnNE5CTCgANU3qLhMRERH/a/R2lqUmRJhciZghJ9WzI7eyTtcXRU6VwjIRk+Sk+cbydJ30Dg0REREzldd1MuhwERlmIzM5yuxyRI5p7rREslOj6Btw8sxbZWN67a6SJgAKsuKIDLef1PtnpRw+5xMRERHxt8ZWT1iWEq+wbCqalukJy0prO3R9UeQUKSwTMUlGchSGAd19Q7R3D5hdjoiIyJj5RjAW5sRjsWiZuAQmwzC48pxCAP7zegl9A45Rv3Z7sScsm38SIxh9slI8QbLCMhERERkP6iyb2nLTYrBaDDp7Bmlu7ze7HJGgprBMxCShditpCZEAVGvpu4iIBKEDFd6wLFcjGCWwnbkwk/SkSDp7BnluQ/moXuN0utiyrwGAJTNTT/q9faO3qxt1viciIiL+5XK5h3eWJcdrZ9lUFGK3Dp9vltS0m1uMSJBTWCZioqxUz53GlbrTWEREgtD+8lYAirSvTAKc1Wrho+fMAODx1w6OanfZ3vJWunqHiI6wMzs/4aTfOzvFF5bpfE9ERET8q6N7gCGHC4sBSXEKy6aqgqxYAA5Vt5tbiEiQU1gmYqKcVO2wEBGR4NTS0Udtcw8WA2bnJ5pdjsiIzlqSTWZyJB3dgzz2ysERn79hZy0Ay2anYbWe/K9Nvpuj6lp6GXK4Tvo4IiIiIu/X4B3BmBAbju0UzlckuE3PigPgYGW7qXWIBDt9FxUxkRa+i4hIsNp5qBmAaVlxRIbbTa5GZGQ2q4VPXzwHgMdfPTS8c+9YhhxOXt9WDcCZizJP6X0TYsIID7Xhcrmpa9YoRhEREfGfplbPCEbtK5vaZuV5piDsr2jF6XKbXI1I8FJYJmKinDSFZSIiEpx2ecOy+QVJJlciMnor56Zx+oIMnC43dzy8lb4BxzGft3FXHV29QyTGhrGwMOWU3tMwDLK93WVV2lsmIiIifuTrLNO+sqktLz2G8FAbvf0OKus7zS5HJGgpLBMxUVaK58JJW9cA3b2DJlcjIiIyertKPGHZvOkKyyR4GIbBV69YQFJsGLXNPdz5j204nUeORnS53Dz6smdM4/krcrFajFN+X980gWrdICUiIiJ+1NjqCctS49VZNpVZrRaKcj17pPeWtphcjUjwUlgmYqKIMDtJsWEAVDXoTmMREQkOjW291Lf0YrEYzM5PMLsckTGJigjh69csxWa1sHFXHXc98u4R42rWba6kvK6T8FAbHzxjml/e03eDVLU6y0RERMSPGoc7yxSWTXVzCzx7pN8tbjK5EpHgpbBMxGTZqd5RjI2601hERIKDbwTjjKw4IsK0r0yCz5xpiXzrU0uxWAxe21rNt367nte2VvGf1w/xhyd2AfDRcwuJjgjxy/vpfE9ERETGgy8sS03QGMapbunMVAB2HGxiyOE0uRqR4KSwTMRkwxdPNJZHRESCxPaDnrsVNYJRgtnKuel885NLCQ+1caCijTv+vo0/P7mHwSEnS2el8uGzpvvtvXzne9WN3bi0dF1ERET8wO1209DaB0BKgjrLprppmbEkxITSP+hkj0YxipwUm9kFiEx1vosnlQrLREQkCDhdbrbtbwRg8cwUk6sROTWr52dQlBPP02+WsvNQMzarhTMXZXLhafl+2VXmk5YQgc1qMDDopLm9Txe0RERE5JR19gwyOOTpIEqOU2fZVGcYBktmpvLSO5Vs2dfIwkL9riYyVgrLREw2fKexwjIREQkCh6ra6OwZJCLMxqw87SuT4JcUF861l8wZ1/ewWi2kJ0VR1dBFVWOXwjIRERE5ZQ2tnhGMCTFh2G1Wk6uRQLBkli8sa+Dzl801uxyRoKMxjCIm84VljW199A04TK5GRETkxLbs83SVLSpMwWbVqaTIaGWnRgFQ1dBtciUiIiIyGdQ2ec4p0pMiTa5EAsXCGclYLQY1Td3UNfeYXY5I0NEVDhGTxUSGEBcVCkBNoy6eiIhIYNuyvwGApbNSTa5EJLhkp/j2lmmagIiIiJw6XxiSobBMvCLD7cyZlgjAmztqTK5GJPgoLBMJAFneO421t0xERAJZW2c/h6raAViifWUiY5LlnSZQpfM9ERER8YPaFk9Yps4yea+zl2QB8PLmStxut8nViAQXhWUiAWB4b5nuNBYRkQC2eZ+nq6wgK5b4mDCTqxEJLtkpGsMoIiIi/lPX5OssizK5Egkkp83PIDTESk1TD7tLW8wuRySoKCwTCQC+sTyV9QrLREQkcL253TPKY9W8dJMrEQk+mSlRGAZ09Q7S0T1gdjkiIiIS5Gp9YxiT1Vkmh0WE2Vm7JBuAf79y0ORqRIKLwjKRAJDj7SzTGEYREQlUHd0D7DjUDMAZCzNNrkYk+ISF2EiOjwA0ilFEREROTXfvIF29gwCkJSoskyN9+KzpWAzYur+RstoOs8sRCRoKy0QCQG56DAD1LT309g+ZXI2IiMjRXt1ajcvlZnpWrEa9iJyk4VGMjRrFKCIiIifP11WWEBNKeKjN5Gok0KQnRbJ6gecGx3+/csjkakSCh8IykQAQFx1KYmwYbjeU1XaaXY6IiMgR3G43z28sA+D8lXnmFiMSxIb31KqzTERERE6BLyxL101schwfOXs6AOu3V1NZr2uNIqOhsEwkQBRkxgFQWqP2aBERCSy7SpqpaeohPNTKmkUawShysrK8e2o1hlFERERORZ1vX1mSRjDKsRVkxbFqXjouN9z/zF7cbrfZJYkEPIVlIgFiWmYsACU17eYWIiIi8j7PbSgH4KzF2USE2c0tRiSIZadqDKOIiIicutpmz7lEusIyOYFPXjgLq8Vg894G3txea3Y5IgFPYZlIgCjI8oZl1eosExGRwNHQ2svGXXUAXHhanrnFiAQ53xjG5vY++gYcJlcjIiIiwepwZ5nGMMrxZadGc9W5hQD8/omddHQPmFyRSGBTWCYSIHxjGKsauhgccppbjIiIiNc/XtyP0+VmwYwk8jNizS5HJKhFR4QQFxUKQHWjRjGKiIjIyalt8oZlyeoskxO74pxC8tJj6OwZ5HeP7dA4RpETUFgmEiCS4sKIiQzB6XJTocWbIiISAIor23hlSxXgGeEhIqcuyzeKsUGjGEVERGTs2rsG6OodxDAgPVFhmZyY3Wbhxo8twmY12Lirjpc3V5ldkkjAUlgmEiAMwzi8t0yjGEVExGROp8t75yGcvSSLotwEs0sSmRSyUzyjGNVZJiIiIifDd4N1WkIkYaE2k6uRYFCQFccnLpgJwH3/2Ul9S4/JFYkEJoVlIgGkwBeW1SgsExERcz25vpTSmg4iw+189oNzzS5HZNI43FmmsExERGQq6uge4L9vlPDEa4doausb8+t9YVlOWrS/S5NJ7PKzZzA7P4G+AafGMYoch8IykQAyIzsegOKKNpMrERGRqeytnbXc//QeAD598WziokNNrkhk8vB1liksExERmXpaOvr4nzte5U//3c1fntrDDXe8yr6y1jEdo7Lecw6Rmx4zHiXKJGW1GPzvVYuw2yxsL27itW3VZpckEnAUlokEkJl5nrCsvK6D3v4hk6sREZGppqN7gD/+dxc/f3AzLjecuyyHD6zMNbsskUnFdxd4XXMPA0NOk6sRERGRieJ2u7nj4W20dg6QGBtGVkoUPX1D3Hb/Jlo7+0d9nPI6T2dZrjrLZIwykqP42HlFAPzpv7vp6h00uSKRwKKwTCSAJMaGk5IQgcsNB9RdJiIiE2RgyMn3fr+BT//gBZ58oxSXGy5Ymcv1Vy7AMAyzyxOZVBJiwoiNCsHlhgrvxS4RERGZ/HaXtLCrpBm7zcLtXzmdO/9vDfkZMXR0D/L7x3eO6hhOl/twWKbOMjkJHz5rOjlp0XT2DPLvVw6aXY5IQFFYJhJgZuUmALCvfGxt+CIiIiert2+I3aUtOF1uCrJi+cF1q/jqFQuwWnWqKOJvhmGQn+7ZU1tWq7BMRERkqnj8tUMAnLc8h/SkSMJCbNz0iSVYDNi4q449pS0jHqO6sYuBQSdhIVayUtRZJmNnt1m49uLZADy1vpSWjrHvzROZrHQFRCTAzC1IBGDHwSaTKxERkakiPiaMv3z3PP70nfO488Y1LJ6Zoo4ykXGUn+kLyzpMrkREREQmQltXP9v2NwBw2ZkFwx/PS4/hvBWesed/f2H/iMc5VNUOQEFWHFaLztfl5CydlcqsvAQGHS4eeanY7HJEAobCMpEAs6goBYD9FW309GlvmYiITIz4mDBSEyIUkolMgPwMz9gkhWUiIiJTw5vba3G5oTAnjozkqCMe++i5hdisBjsPNbO37MTdZb6wbHpW3DhVKlOBYRh86qJZALy4qULdZSJeCstEAkxqQgSZyZG4XG52HlJ3mYiIiMhkk59xeAyjy+U2uRoREREZbxt31QFwxsKsox5LiY9g7dIcAB5Zd+IunwOVnv3207Pj/FugTDlzC5KYnZ+A0+XmhbcrzC5HJCAoLBMJQItnpgLw9u56kysREREREX/LSonCZrXQN+Cgsa3X7HJERERkHPUNONhX7ukYWz479ZjPuWLtDCwWg237GzlY1XbM53T3DlJS3Q7APO8KD5FTccnqaQC88HY5Tt3AJaKwTCQQrZ6fAcDbu+sYHHKaXI2IiIiI+JPNaiEnLRrQKEYREZHJbtehZhxON6kJEaQnRR7zOelJkaxZlAlw3B1Su0qacbk9N90kxoaPW70ydaycl05UuJ3WzgH2lDabXY6I6RSWiQSgWXkJJMaG0dvvYNuBRrPLERERERE/m+YdxVha02lyJSIiIjKeth/0rNhYXJRywv3AV55TiGHApj31x7yZ5t1iz3EWzkgen0JlyrHbLJzmvWH/jXdrTK5GxHwKy0QCkMVicPoCzx1F67frh5WIiIjIZJOfEQNAaY06y0RERCazPSWeEYzzpied8HnZqdHDk4b+9b7dZU6Xm7e9e88Wz0wZhyplqjpjoefv3IaddTicLpOrETGXwjKRAOX7YfXOnnr6Bx0mVyMiIiIi/jQ9Ow6Ag1VtuN3aESEiIjIZ9fQNUVbnuTFmzrSR94x99NxCAN7aWUtVQ9fwx/eUNtPWNUBUuJ2FhQrLxH/mFSQRFxVKV+8gO7xdkCJTlcIykQBVmBNPSkIE/YNONuysNbscEREREfGjgqw4LBaDtq4Bmtv7zS5HRERExsG+8lbcbkhPjCQhJmzE5+dnxLJiThpuNzz68uHushfergBg1bx07DZdzhX/sVotnDY/HdB0KxF9dxUJUIZhcMGKXACeWl+qO45FREREJpFQu5W8dM8oxuKqNpOrERERkfGwv6IVgFn5CaN+zVXnebrLXt9WzZ7SFirqOodDjItX5/u/SJnyzlyUBcDbu+oYcjhNrkbEPArLRALYBStzsdssHKruYHuxWqFFREREJpPCnHgADlQoLBMREZmMSqo9IxgLveOXR2NGdjxrl2bjcsP3/7CBG+98HbcbVs5NoyBr9McRGa1ZeQkkxobR0+9g2/5Gs8sRMY3CMpEAFhsVyoWr8gB48Nm96i4TERERmURm5XnCsj2lzSZXIiIiIuOhpLodYMwh1xc/PI+i3HgGHS4cThfZqVF85YoF/i9QBLBYDE5fkAnAGxrFKFOYzewCROTErjynkJfeqeBQdQcbdtaxekGG2SWJiIiIiB/MLUgC4FB1B739Q0SE2U2uSERERPylpaOPtq4BLAbkZcSM6bURYXZ+fv0ZvFvcyOCQi0WFyYSF6jKujJ8zFmbw3zdK2Ly3noEhJ6F2q9kliUw4dZaJBLi46FA+tGY6AA88s5f+QYfJFYmIiIiIP6TER5CWGIHL5WZvWavZ5YiIiIgf+UYwZqVGExYy9qDLYjFYMjOVVfPSFZTJuCvMiSc5Ppy+ASdb9zWYXY6IKRSWiQSBD60pICEmjLqWHh54eq/Z5YiIiIiIn8zzdpeNZj+t2+3mjXer+eGf3+b7f9jAsxvKcLo0pltERCQQ+UYwTteeMQkChnF4FOObO2pHfP7+8lYefbmYHaM4hxUJFgrLRIJARJid/71qEQBPv1WmZZsiIiIik8SSWakAvLO3/oT7ad1uN79/fCe/eGgrm/c28G5xE/f+eye33/+OAjMREZEAdMjbWVaQFWtyJSKjc7p39cs7e+tPONnqsVcO8o271/Pgs/v47h828OKmiokqUWRcKSwTCRKLZ6Zwyep8AO78xzZaO/tNrkhERERETtWiwmRsVgt1zT1UN3Yf93nr3qnk2Q3lWAz4yNnT+eSFswixWdi0p55/vnhgAisWERGR0SipaQegIDPO1DpERmtGdhypCREMDDrZvOfYoxi37GvggWc8U68SY8MAuPffO2np6JuwOkXGi8IykSBy7QfnkJceQ3v3AL98aCtOp8vskkRERETkFESE2Zk/3TOK8XgjbyrqO/n9E7sAuObCWVx7yRw+em4hN3x0IeC5u7e+pWdC6hUREZGRtXX109LRj2HAtEx1lklwMAyDNYuzAHhhU/lRj/f2D/HbR7cDcNFpefz1e+czKy8Bh9PF02+WTWClIuNDYZlIEAm1W/nWp5YSHmplV0kz/9BdxCIiIiJBz3dR4pUtlbjeN1Kxf8DBzx7czOCQk0WFyXzk7BlHvG5hYTIOp4uHX9g/oTWLiIjI8ZV4RzBmJkcRHmozuRqR0btgRS6GATsONlPV0HXEYw+/sJ+Wjn7SEiP47KVzMQyDy8+eDsALb5frpn4JegrLRIJMVko0X71iIQD/erlY+8tEREREgtxp89IJD7VR39LLtgNHntv9/omdVDV0kxATyk2fWILFYgw/ZhgGn7poFgDr362huV3jb0RERAJBSXU7ANOz4kytQ2SsUhIiWD47DYBHXioe/vjBqjaeXl8KwJcvX0Co3QrAstlpREeE0NU7xL7y1okvWMSPFJaJBKE1i7O4cFUebjfc8fetujAiIiIiEsTCQm1csDIXgL8+vYchhwu3282/1hXz8uYqLAZ8/eqlxEWHHvXaGdnxzC1IxOly8/zb5RNcuYiIiBzLIW9YVqCwTILQx84vAuCN7dXsLmmmt3+IOx7eissNZy7MZPHMlOHnWi0GS7z/vWXfsfeciQQLhWUiQerzl81lWmYsnT2D/OKhLWp1FhEREQliV51bSHRECJX1Xfz0gc3c8fA2/vbcPsCzp2yed6/ZsVywMg+AN7bV4Ha7j/s8ERERmRiHvGMYC7K0r0yCz/SsONYuzcbthlv/9DZf+unL1DT1kBgbxpc+Mv+o5y+dlQrAVk2/kiCnsEwkSIUM7y+zsbesdfhiioiIiIgEn6iIEP7v44swDHhnbz2vv1uNYcB1l83lynMKT/jaFXPSCLFbqWvp4WBV+8QULCIiIsfU0T0wPAGoIFNhmQSnL18+nxnZcQwMOmnrGiA6IoTvfXYF0REhRz13vvemror6Tnr7hya6VBG/0YZJkSCWkRTF/161iJ8+uJl/v3qIOdMSWeadKywiIiIiwWXZ7DRu/fwqXnynAoDzluewZGbqiK8LD7WxYk4a67fX8Ma7NRTmxI93qSIiInIcJd6usoykSCLC7CZXI3JywkJt/Oz601n3TiV9Aw7WLM4iMTb8mM+NjwkjJSGCxtZeDla2s6AweYKrFfEPdZaJBLnVCzK4ZHU+AHf+4126ewdNrkhERERETtbimSnc/Kll3PypZaMKynzWLMoEYP32apwujWIUERExS0lNO+AZZScSzOw2Kxeels/lZ884blDmM9N7s9b+itaJKE1kXCgsE5kEPnvpHLJTo+nqHeSfLxWbXY6IiIiITLDFM1OIDLfT2jnA3rIWs8sRERGZsg5VtwNQoLBMppCiPF9Y1mZyJSInT2GZyCRgt1n5/GVzAXj6zVJqmrpNrkhEREREJpLdZmXZbO9y9X0NJlcjIiIydR3yjmEsyNK+Mpk6CrM9YVlpTYfJlYicPIVlIpPE4qIUls5Kxely89en9phdjoiIiIhMMN/Yxq37G02uREREZGrq6h2ksbUXUGeZTC256TEYBrR29tPeNWB2OSInRWGZyCTy2Q/OwWIx2LSnnh3FTWaXIyIiIiITaFFhMoYB5XWdtHT0mV2OiIjIlFPiHcGYlhhBVLjd3GJEJlB4qI2MpEgASmvVXSbBSWGZyCSSnRrNxavzAfjTk7u13F1ERERkComNCmVGdhyg7jIREREzHB7BGGduISImmJYZB0CZRjFKkFJYJjLJfPz8IqLC7ZTXdfLSpgqzyxERERGRCeQbxbhNYZmIiMiE83WWFWRqX5lMPfkZMYA6yyR4KSwTmWSiI0L4+AVFADz0/D56+oZMrkhEREREJsqSmSkAbC9uxOl0mVyNiIjI1FLi7Sybrs4ymYJyUqMBqG7oNrkSkZOjsExkErrotHwyk6Po6B7kX+uKzS5HRERERCbI9Ox4osLt9PQ7OOS9u11ERETGX1fvIHUtPYDGMMrUlJ3mDcuaunFpNYwEIYVlIpOQzWrhc5fOAeDJ9SXUNuuODhEREZGpwGoxmDc9CYCdh5pNrkZERGTqKK5sAyA9KZKYyBCTqxGZeKkJkdhtFgaHnDS29ZpdjsiYKSwTmaSWzkplcVEKDqebvzy5x+xyRERERGSCzPeFZQcVlomIiEyU4gpPWFaUE29yJSLmsFoMMpOjAKhu1I37EnwUlolMUoZh8PnL5mKxGGzaU8/2Yi15FxEREZkKfGHZ3rIWhhxOk6sRERGZGg54O8sKFZbJFJaV4gnLKuu7TK5EZOwUlolMYtmp0Vy8Oh+AP/53Nw4teRcRERGZ9LJTo4mLDmXQ4WK/9y53ERERGT9ut5viynYAinIVlsnUlZ3q3VvWqLBMgo/CMpFJ7uPnFxEdYaeyvou/v7Df7HJEREREZJwZhsH8Ao1iFBERmSj1Lb109Q5is1rIz4gxuxwR02SneMKyqgaFZRJ8FJaJTHLRESF8+SMLAHjslYPsKtEFExEREZHJbv4MT1imcz8REZHx5xvBOC0zBrvNanI1IubJSvWMYaxq7MbtdptcjcjYKCwTmQLOWJjJuctycLvhVw9vpat30OySRERERGQczZ+eDMCBilb6BxwmVyMiIjK5FWtfmQgAmclRWAzo6RuivWvA7HJExkRhmcgU8YUPzyMjKZLmjn7u/td23d0hIiIiMomlJUaQHB+Ow+lmb3mr2eWIiIhMar6wrEhhmUxxIXYrqQmRAFRpb5kEGYVlIlNEeKiNr1+zBJvVYOOuOh5/9ZDZJYmIiIjIODEMg/nTfXvLmkyuRkREZPIacrgorekAoDBXYZnI8CjGhm6TKxEZG4VlIlPIjOx4rvvQPAAefHYvO4p14URERERkshoOyw5pb5mIiMh4KavtYMjhIjrCTnpipNnliJguKyUagGp1lkmQUVgmMsVcuCqPc5Zl43LDzx/aQmNbr9kliYiIiMg4mFfg2VtWUt1OT9+QydWIiIhMTr4RjDNy4jEMw+RqRMyXleLpLKtpVGeZBBeFZSJTjGEYfPkjCyjIiqWzZ5Bf/X0bTpf2l4mIiIhMNsnx4aQnRuJyw96yFrPLERERmZS0r0zkSL6wrLpJYZkEF4VlIlNQqN3Ktz65jPBQK3tKW3jh7XKzSxIRERGRcTBPoxhFRETGlS8sK1RYJgJAZrInLGtq66N/wGFyNSKjp7BMTprL5eLPf/4z5513HvPmzePCCy/koYceOuFr1q1bR1FREZs2bTri4y+99BLnnHMOK1as4LbbbsPpdB7x+O233853v/vdUdV18803s3bt2uM+vnbtWm6++ebh//7kJz9JUVHR8D8zZ85k0aJFXH755Tz44IM4HEd+U7/77rspKioaVS2BLD0pkk9dNBuAv7+wn95+jeYREREJVjovk+PxhWW7ShSWiYiI+Ft37yA1TT2AwrLR0Dnr1BAbFUp0RAgAtc09JlcjMno2swuQ4PXTn/6UBx54gI997GOcd955VFZW8utf/5rq6uojfoD4tLW1ccsttxz18dbWVr7xjW/w6U9/mnnz5vG9732PgoICPvaxjwFQXV3N448/ztNPPz1un8vs2bOHa3M6nXR0dPDGG29w++23s2XLFu666y4slsmXLX9gVR5Pv1lKTVMP/371EJ+8cJbZJYmIiMhJ0HmZHM98b1hWWtNBd+8gUd4LFyIiInLqiivbAUhPjCQmUj9jR6Jz1qkjKyWKfeWtVDd2MS0z1uxyREZFYZmclNbWVh566CGuvPJKfvCDHwx/PD09na985StceeWVFBQUHPGaH/zgB9hsR/+V27ZtG1arlRtvvBHDMHj77bfZsGHD8A+4u+66i6uuuorU1NRx+3yioqJYuHDhER9bu3Yt06ZN47bbbuPpp5/m0ksvHbf3N4vNauHTF8/mJ/dv5j+vl3Dx6nwSYsLMLktERETGQOdlciIJMWFkJkdR09TN7tIWVs5NN7skERGRSaO4SiMYR0vnrFPL4bBMe8skeEzdeFtOSXl5OU6nk7PPPvuIj69YsQKXy8X69euP+Pizzz7Lhg0b+MY3vnHUsQzDICQkBMMwALDb7bhcLgD27t3L+vXr+cIXvjBOn8mJXXPNNaSmpvLPf/7TlPefCCvnplOUG8/gkJOn1peaXY6IiIiMkc7LZCS+7rJd2lsmIiLiVwcqvGFZbpy5hQQBnbNOLVkpnr1lNQrLJIgoLJOTEh/vuWOmtrb2iI9XVlYCnnZnn+bmZn7wgx/w//7f/yM5OfmoY82dO5euri7WrVtHQ0MDr732GkuWLAHgF7/4Bddddx0xMTFjrtHhcBzzn7GwWCysWrWKnTt3jvm1wcIwDK5YOwOA5zaU0afFmyIiIkFF52UyEt/esp0Ky0RERPzG7XZTXOkJy4rUWTYinbNOLVkp0QDqLJOgojGMclLy8/NZsmQJd999N2lpaaxcuZKqqiq+973vERISQm9v7/Bzv/e977Fo0SI+9KEPHbWMEyA1NZVbb72Vb37zm/T393PBBRdw9dVX8+abb1JaWsrvf/97HnvsMR544AHi4uL49re/zezZs09YX01NDXPmzPHL55qUlMTQ0BDt7e0kJSX55ZiBZvnsNNKTIqlr7uGtHTWcuzzX7JJERERklHReJiOZV+D5WpXXddLRPUBsVKjJFYmIiAS/htZeOnsGsVkN8jO0k2kkOmedWjJ9nWXN3bhcbiwWw+SKREamsExO2m9+8xu+//3vc/311wMQExPDN77xDe6++27Cw8MBeOKJJ9i6deuICzWvuOIKLr/8coaGhggNDcXlcvHLX/6S66+/nrKyMm677Tbuu+8+9u7dy5e+9CXWrVtHSMjxF6cmJydz7733HvOxL3/5y2P6PN1uN8Bwa/dkZLEYnLc8hwef3cdL71QqLBMREQkyOi+TE4mLDiU7NZqqhi52l7awen6G2SWJiIgEPd8IxvyMWELsVpOrCQ46Z506UhMisFkNBgadNHf0kRIfYXZJIiNSWCYnLSkpiXvuuYfOzk4aGxvJycnBYrFwyy23EBsbS319Pbfddhs333wzCQkJOByO4fnBLpcLp9OJ1Xr4ZMJisRAa6rnL9cknn2RwcJDLL7+c3/72tyxdupRly5axZMkS7rrrLrZv387y5cuPW1tISAjz5s077mNj0dDQQFhYGHFxcWN6XbBZuzSbh57bx96yVmqauslMjjK7JBERERklnZfJSOZPT/KEZYeaFZaJiIj4QXGVRjCOlc5Zpw6b1UJ6UiRVDd1UN3YrLJOgoJ1lctKeeeYZ9u/fT0xMDNOnTyckJIR9+/bhcrmYPXs2GzZsoKuri+985zvMmTOHOXPmcO211wJw7bXXct555x3zuIODg/zmN7/hpptuwmq10tLSQmysp53dYrEQFRVFc/PE7FtwOBxs2rSJxYsXH/HDeDJKjA1n8cxUAF7aVGFyNSIiIjIWOi+TkQzvLSvR3jIRERF/KPZ2lhXmKiwbLZ2zTi2+G/FrtLdMgoQ6y+Sk3XvvvRQWFvKrX/1q+GP3338/0dHRrFixAofDwWOPPXbEa/bs2cMtt9zCD37wAxYtWnTM4/7tb38jJSWFc889F4DExMThZZ+Dg4O0t7eTkJAwTp/VkR555BGampr4/ve/PyHvZ7bzV+SwZV8Dr2yp4pMXzsJqVZ4uIiISDHReJiOZOy0RgMr6Ltq7BoiL1t4yERGRkzXkcFFS0wGos2wsdM46tWSlRAP1VDd2mV2KyKgoLJOT9slPfpJbbrmFGTNmsGjRIp599lmefvppbr31VqKjowGIjz/yhMG3rDM/P5+ioqKjjtnR0cEf/vAH7rnnnuGPnX322dx333088cQTFBcXExMTw8KFC/36uXR3d7N9+3bA09bd1tbGm2++ySOPPMKll17K+eef79f3C1RLZ6URGxVCW9cAWw80snx2mtkliYiIyCjovExGEhsVSl56DOV1newqaeaMhZlmlyQiIhK0yus6GHK4iAq3k54UaXY5QUPnrFOLr7OsWp1lEiQUlslJu+qqq+jv7+ehhx7iD3/4A/n5+dxxxx1ccsklJ33MP/zhDyxatIilS5cOf2z+/PncdNNN/PznPyc2Npa77rqLsLAwf3wKw/bu3ctVV10FeJZvRkZGUlhYyK233sqVV17p1/cKZHabhbOXZPOf10t4aVOFwjIREZEgofMyGY3505M8YdkhhWUiIiKnoriyHYDCnHgMwzC3mCCic9apJSvVO4axSWGZBAfD7Xa7zS5CRAJHRX0n1//iVawWgwduuYDYKI3oEREREZkM3t5dx21/fYfM5Ch+f/M5ZpcjIiIStO78xzZe2VLFx84r4uoPzDS7HJGA1N07yMe/9xwAj9x2ERFhdpMrEjkxLSQSkSPkpsUwPTsOp8vN6+9Wm12OiIiIiPjJ3GmJGIbn7t6Wjj6zyxEREQlaByraACjK1b4ykeOJiggh3rsnt7JBe8sk8CksE5GjnLs0G4CXN1eZXImIiIiI+EtURAjTMmMB2FXSYnI1IiIiwam7d3B4rNyM7DhzixEJcPkZnnPP8tpOkysRGZnCMhE5yhmLsrBZLZTWdFBW22F2OSIiIiLiJ/MKkgDYdajZ5EpERESC08GqdgDSEiO0ukJkBHnpMQC6vihBQWGZiBwlJjKEFXPSAHjpnUqTqxERERERf5k/3RuWlSgsExERORnFlZ4RjIU5GsEoMpL8DE9YVl6nzjIJfArLROSYzluRA8ArmyvpH3CYXI2IiIiI+MPs/EQsBtQ199DY2mt2OSIiIkHngDcsK1JYJjKiPN8YxrpO3G63ydWInJjCMhE5pkWFKaQlRtDT7+C1bdVmlyMiIiIifhAZbmdmXgIAm/c1mFyNiIhIcHG73Yc7y3IVlomMJCslihCbhd5+B7XNPWaXI3JCCstE5JgsFoOLV08D4PFXD+F0ukyuSERERET8Yflsz7jtd/bWm1yJiIhIcGls66OjexCb1WCat2NGRI7PZrVQkBUHwIGKVnOLERmBwjIROa4PrMwlOiKEupYeXt5SZXY5IiIiIuIHy2anArDzYDN9GrctIiIyasUVnq6yvIxYQuxWk6sRCQ5F3i7MA97/f0QClcIyETmusFAbHz13BgAPPLOXzp5BkysSERERkVOVnRpNWmIEDqeL7cVNZpcjIiISNLSvTGTshsOySoVlEtgUlonICV1y+jSyU6Pp7Bnkjr9v1ThGERERkSBnGAbLvKMYN2sUo4iIyKgN7ytTWCYyajNzPftyy2o66O7VjfgSuBSWicgJ2awWvnHNEkLsVrbtb+Rnf9tCTVM3vf1DVDd2seNgE+8eaGRfWSsDQ06zyxURERGRUVjuHcW4eV8DLpfb5GpEREQCn8PpoqS6HTjcKSMiI0uKCyczOQqXG3Yeaja7HJHjspldgIgEvvyMWL55zRJuf2AzG3fVsXFX3TGfFx5q48NrCrjinELsNmXxIiIiIoFqzrQkwkNttHcNcKi6XXfIi4iIjKC8rpNBh4vIcDvpiZFmlyMSVBYVJlPT1M324iZOm59hdjkix6Sr2SIyKivmpnP7V05nXkESNqvnW0dYiJWslCjy0mOIjw6lb8DB3188wM2/W09bV7/JFYuIiIjI8dhtFhYXpQDwjkYxioiIjGh4BGN2HBaLYXI1IsFlkfe8U1MNJJCps0xERm1WfgI/+cpqnC43DqeLEJsFw/CcILpcbt7cUcO9/95JcWU73/7dW/zif84gOiLE5KpFRERE5FiWzU7lrZ21bNxVx9UXzBw+rxMREZGjHajwhmUawSgyZgsLk4kIs9Hc3sfeshbmFiSZXZLIUdRZJiJjZrUYhNqtR1xQsVgMzlyUxS//90ySYsOoaermtr++w6D2mImIiIgEpBVz0rDbLFTWd1FS02F2OSIiIgHN11lWpNHFImMWYrdy2jzP+MVXtlSZXI3IsSksExG/ykyO4pbrVhERZmNPaQv3/nun2SWJiIiIyDFERYSwYk4aoIsWIiIiJ9LTN0R1YzeA9nyKnKRzl+cA8OrWKhrbek2uRuRoCstExO/y0mO4+VPLsBiwbnMlr22rNrskERERETmGc5Z5Llq8trWaIYfL5GpEREQC08EqT1dZakIEsVGhJlcjEpzmTEtk/vQkHE43v3tsB06nzj0lsCgsE5FxsagohY+eWwTAPY/toL6lx+SKREREROT9FhUmEx8dSlfvIFv2NZhdjoiISEA6oBGMIn7x2Q/OIcRuZdv+Rr7z+w0882YpL26qYNv+Rjq6B8wuT6Y4hWUiMm4+dl4hs/IS6Btw8MuHtuLQHSMiIiIiAcVqtXD2kmwAnnmr1ORqREREAlNxRTsAhbkKy0RORUFWHN/61FLCQqzsKW3h90/s4u5/beeWP27kMz96kQee2atpB2IahWUiMm6sVgtfv3oJkeF2DlS28ei6YrNLEhEREZH3uWh1PhaLwY6DzRyqaje7HBERkYDidrvZX9EKQJHCMpFTtnx2Gr++6Sw+tKaAlXPTWDIzhfSkSIYcLh575SC33LeR3v4hs8uUKUhhmYiMq5SECL58+XwA/vVyMeV1nSZXJCIiIiLvlZoQwZkLMwF4+IX9JlcjIiISWKobu+nsGSTEbqUgM87sckQmhYzkKD536Vy+85kV3HrdKv5w8zl8+9PLCA+1saukme/ft5HuPgVmMrEUlonIuDtzUSYr5qThcLr59SPvaoGniIiISID5+PlFWC0GW/Y1aHeZiIjIe+wtawE8+8rsNl1KFRkPhmFw2vwMfvyl04gKt3Ogoo3v/2EDPQrMZALpO7yIjDvDMPjyR+YTGW7nUFU7/3m9xOySREREROQ9MpKjuHh1PgB3/mMbze19JlckIiISGPaWeUYwzs5PMLkSkcmvMCeen3xlNdERIRysatdIRplQCstEZEIkxobz+UvnAp7xPtWNXSZXJCIiIiLv9emLZzMtM5bOnkF+9uBmXZgQERHhcGfZ7PxEkysRmRryM2L58ZdOIzrCzoHKNgVmMmEUlonIhDlnWTaLi1IYcri4+1/bcbncp3S8nr4h/vifXXzhJ+v4zr1vsetQs58qFREREZl6QuxWbv7UMiLDbOyvaON/7niNlzZV0Njai8Ppwul00T/goLd/iIEh5ymfy4mIiAS6lo4+6lt6sRgwMy/e7HJEpoxpmbH88IunERluZ3+FJzBr6dDkAxlfhtvt1m84IjJhGtt6+erPX6F/0MmNH1vEOctyTuo43X1DfPt3b1Je1zn8MYsBX7t6CWcuyvJXuSIiIiJTTnFlG7c/sHnEUYx2m4WU+HBSEyJJTYwgLSGChNhwBoec9PY76O4dpL17gPauAZwuN/HRoSwqTGHlvHTtfBERkaCwfnsNP//bFqZlxvLrm84yuxyRKedQVTvf9e4ui46w88UPz+fMRZkYhmF2aTIJKSwTkQn3+KuH+OvTe4iNCuH3N59LVLh9zMe48x/beGVLFfHRoXz20rls3dfAa9uqsdss/OrGNeSlx4xD5SIiIiJTQ9+Ag2feKuP1bdVUN3bjcLr8duzk+HD+56MLWViY4rdjioiIjId7/72DZzeUc8np+Xzxw/PNLkdkSqpu7OKXD2+lpLoDgKKceD518SzmT082uTKZbBSWiciEczhd/M8dr1HV0MUlq/P54uVjO+F8Z289P/rzJgwDfvbVM5iVn4DT5eZHf36brfsbWTAjiR998TTdZSIiIiLiBy6Xm67eQSwWA7vVgsVi4HC66OwZpKG19/A/Lb20dfUTGmIlItROZLiNuOgw4qJCsFkt1DR188qWKtq6BjAMuOkTSzhrsSYCiIhIYHK73Xzh9nXUt/Ty3c8sZ8XcdLNLEpmyhhwuHnvlII+/epD+QScAcwsS+ewH5zAjWyNSxT8UlomIKXYeauI7927AYjH4zdfOIjdtdJ1gfQMOvvTTl2nt7OfDZ03nsx+cM/xYfUsPX/7ZKzicLr732RUsn5M2XuWLiIiIyEnoH3Rw77938sqWKiwWg5999XRm5iWYXZaIiMhRqhu7+PLPXsFmtfD3H11IeKjN7JJEpry2zn4eWVfMC29X4HC6MAz4wMo8PnnRLKIjQswuT4KcBsWLiCnmT09m1bx0XC43f/rvbkab2//3jRJaO/tJS4zg6g/MPOKxtMRILjtzGgB/eWq3X8cFiYiIiMipCwux8b9XLWL1ggxcLjd3/H0rvf1DZpclIiJylK37GwGYOy1RQZlIgIiPCeNLl8/nvm+fy1lLsnC74bmN5Xz5Zy+z61Cz2eVJkFNYJiKm+ewH52CzWthe3MSmPfUjPr+je4DHXz0IwKcunE2o3XrUcz56biExkSHUNPXw2tYqv9csIiIiIqfGYjG4/sqFpMSHU9/Sy33/2WV2SSIiIkfZsq8BgCWztGNTJNAkx4fztU8s4favrCYnLZqO7kG+f98G3hnF9UWR41FYJiKmSUuM5ENrCgD4wxO7Rryr+JF1xfQNOJmeFcvqBRnHfE5EmJ2PnD0dgH+tO4hT3WUiIiIiAScq3M5Nn1iCxYCXN1exr6zV7JJERESG9Q842F3SAsCSmakmVyMixzO3IIlf3biG0+an43C6+emDm9lfofNKOTkKy0TEVFedV0hqQgTN7X089Pz+4z6vqqGLZ98qA+DTF8/GYjGO+9yLTssnJjKEupYeXt1a7feaRUREROTUzZmWyDnLcgDPCG2t0xYRkUCx/WATDqeLlIQIslKizC5HRE4g1G7lm9csZfnsNIYcLn76wGZ6+jTmW8ZOYZmImCosxMZXr1gAwNNvlnLgGHd/uN2evWZOl5vls9NYWHjiEQhhoTYuP8vXXVas7jIRERGRAHX1B2YSGmJlf0UbG3bVmV2OiIgIAK9t89x4u3JOGoZx/Jt1RSQwWK0Wvn7NEtKTImnp6OeBZ/aaXZIEIYVlImK6RUUprF2ajdsNv310B0MO5xGPb97bwLYDjdisBp+7dM6ojnnR6sPdZa+/q+4yERERkUCUGBs+PJb7oef24XKpu0xERMzV3TvIpt2evUdrl2abXI2IjFZ4qI3rr/TckP/cxnJ2lzSbXJEEG4VlIhIQPnfpXGIiQyiv6+Sex3YOXyhpbOvlN/96F4BLzyggI3l04w/C39Nd9s+X1F0mIiIiEqguP2s6keF2qhu7eXu3ustERMRc6zZX4XC6yEuPYVpmrNnliMgYzJ+ezPkrcgH405Ma8y1jo7BMRAJCTGQIX/MueV+3uZKf3P8Oz7xZyrd++yYd3YPkZ8Tw8QuKxnTM4e6yZnWXiYiIiASqiDA7l6zOB+DRl4t1UUNEREzjdLl55q1SAC5ena8RjCJB6FMXzSIsxEpJdQeb9zaYXY4EEYVlIhIwFs9M4X8/tgirxWDTnnp+/8Qumtv7yEyO5LufXUFYiG1MxwsPtfFhb3fZA8/s03JPERERkQD1wTOmEWK3cqi6g+3FTWaXIyIiU9SLmyqob+klKtzOWYuzzC5HRE5CbFQoF3tvxPrvGyUmVyPBRGGZiASUtUtz+NWNa1i7NJv505P46LmF/PJ/ziQlPuKkjvfBM6aRkRRJa2c/92u5p4iIiEhAio0K5YKVnpE5j71y0ORqRERkKmps7eVB73WDT1wwk7DQsd2wKyKB46LV+VgM2HmomaqGLrPLkSChsExEAs60zFj+7+OLue3Lq/nkhbOIigg56WOF2q1c/9GFADy/sZx3DzT6qUoRERER8acPr5mO1WKw81Az+ytazS5HRESmkJaOPn70l0109w0xIzuOi07LM7skETkFKfERLJudBniuB4qMhsIyEZn05hUk8YFVeQD89MHNlNV2mFuQiIiIiBwlOT6cs5dkA/DoOnWXiYiIf7ndbspqO3h7dx2vba3ita1VvLKlkj/+Zxdf+fkrlNd1EhcVys2fWobVqkumIsHuQm/o/fLmSvoHHOYWI0FB/cQiMiVcd9lcqhq62FPawq1/3MhPvnI6mclRZpclIiIiIu9xxTkzeGVLJe/sraestoP8jFizSxIRkSDncLp4an0pz20sp66557jPm5YZy7c/vYyUhJNbAyEigWVRYQppiRHUt/Ty1s5azlmWY3ZJEuAMt9vtNrsIEZGJ0N03xM2/XU9FfRexUSHcet0qpmfFmV2WiIiIiLzHL/62hTe213D6ggy+9allZpcjIiJBrLd/iB/+eRN7SlsACLFZyMuIISzEhsUwwIDUhAiWz05j6axULBbD5IpFxJ8eeekADz2/n0WFyfzwi6eZXY4EOIVlIjKltHcNcOufNlJS3UFEmI3vfXYFcwuSzC5LRERERLzK6zq54ZevYhhw99fPJjctxuySREQkCLlcbm7940beLW4iIszGZy6Zw5rFWYSHatCWyFRR19zDF25fh8WA+2+5gPjoMLNLkgCmAbwiMqXERYfyky+vZs60RHr7Hdxy30a27GswuywRERER8cpLj2HVvHTcbvjLk3vQ/Z0iInIynlxfwrvFTYTYrfz4S6fxgVV5CspEppj0pEiKcuJxueHN7bVmlyMBTmGZiEw5EWF2fvCFVSybncqgw8XtD2zmYFWb2WWJiIiIiNe1l8zGZrWw7UCjbmwSEZEx6+wZ5J8vHgDg85fNZUZ2vMkViYhZzlycCcDr71abXIkEOoVlIjIlhdqt/L9rl7NkZgqDQ05++dBWBoecZpclIiIiIkBGUhSXnTkNgD/9d7fO00REZEz+8/ohevod5GfEcP6KXLPLERETnbEgE4sBByraqG/pMbscCWAKy0RkyrJZLXzjmqUkxIRS29zDv189ZHZJIiIiIuL10XMLiY/2nKc9sq7Y7HJERCRIDDmcvLipAoCrzi3CajFMrkhEzBQfE8b8GcmAusvkxBSWiciUFhlu5/OXzQPg0ZeLqW3qNrkiEREREQHP6OwvXj4fgMdeLtY4RhERGZWNu+ro6B4kMTaMlXPTzC5HRALAmkVZALy+rVr7cOW4FJaJyJR3+oIMFhelMORw8bfn9pldjoiIiIh4nTYvnQtW5uJywy8e2kJlfafZJYmISIB7490aAM5ZloPVqkufIgKr5qVjt1moauimvE7nk3Js+okhIlOeYRhce8lsAN7aWUt1Y5fJFYmIiIgIeM7Tvvjh+cyZlkhvv4Pv/n4DZbUdZpclIiIBqrd/iK37GwE4Y2GmydWISKCIDLezdFYq4OkuEzkWhWUiIkB+Riwr5qThdsNjrxw0uxwRERER8bLbLHz708vIz4ihrWuAb//uTd490Gh2WSIiEoC27m/E4XSRlRJFblq02eWISADxjWJ8Y3sNLpdGMcrRFJaJiHh99NxCAF7dWk1Da6/J1YiIiIiIT2xUKD/5yunMzk+gp9/BLX/cyO8e20Fnz6DZpYmISADZXtwEwNJZqRiGYXI1IhJIls5OJTzURlNbH/srWs0uRwKQwjIREa/CnHgWzkjG5XLz/MZys8sRERERkfeICrfzwy+exgdW5eF2w/Mby/nST1/mlS2VJ7WovaG1l2feLOXRl4vZtr8Rp9M1DlWLiMhEcbvdbC/2dB4vLEw2uRoRCTShdiur5qUDGsUox2YzuwARkUBy0eo8th9sYt07lXzigpnYbbqnQERERCRQhNqtfPWKBaxZlMnvH99JRX0Xd/7jXV7dUs2Xr5hPRlLUiMdobO3lXy8Xs+6dSpzvGcGTmRzJ169ZyvSsuHH8DEREZLzUNffQ2NaHzWphTn6i2eWISAA6c1Emr2yp4q2dtXzhQ/OwWnXdTw7T3wYRkfdYNjuN+OhQ2rsHeGdPvdnliIiIiMgxzC1I4q6bzuLTF88mxGZh+8EmvvKzV7j33zto7ew/5mua2vq457EdfPGn63jh7QqcLjdzpiWyZlEWMZEh1DT18P/ueZO9ZS0T/NmIiIg/bD/oGcE4Ky+BsFD1B4jI0RbMSCYmMoSO7kF2HGw2uxwJMPrJISLyHjarhXOX5/Doywd5/u1yVi/IMLskERERETkGm9XCFWtncNr8dP7wxC627W/k2Q3lrNtcxcq5aSybnUZyXDitnf2s317DO3vqhzvJFs5I5hMXzGRWfgIAXb2D/PSBzew81MxP7n+HX990Fomx4WZ+eiIiMka+fWUawSgix2OzWjh9QQbPbijn9XerWTwzxeySJIAY7pMZ7i4iMonVt/TwhdvX4XbDfd8+l/SkSLNLEhEREZER7Cpp5sFn9rK/ou24z5k/PYlPXDCTOdOOHs/VP+jgm3evp6y2k8VFKdx63UoMwxjPkkVExE+cLjdXf+9Zevod3PG/Z1KYE292SSISoPaUtnDz794kPNTG337wAULtVrNLkgChMYwiIu+TlhjJwhmeO9FeeqfC5GpEREREZDTmFSTx8xvO4Bc3nMGHz5pOUU486UmRTM+O47IzC/jt18/mti+vPmZQBhAWYuMb1yzFbrOw7UAj67fXTPBnICIiJ6u8toOefgcRYTYKtHtSRE5gVl4CSXHh9A042LKvwexy5P+3d+dxUZX7H8A/MwzDvojIoiK4AcoioIKIipqatqulaVqppbe82qpm3jZvv2w1FUuvZt5ualkulVqa5pr7viCCIKuA7DvMMDPP7w9iEgFlYIYZ4PN+vXjdPHPOme/3PjzPfJnnnOeYEC7DSERUh/vDvXA+Lhv7TqVg8v2+kBnogZ8ajYAAYCblVctERERETSWRSODr5QRfL6dGHe/haocn7vPGpj3X8L9fYxAe0BHmMl5jSkRk6q4l5QEAfD2d+Pc1Ed2VVCpBZHAnbD0QjwNnUhERyEewUBVOlhER1SG0txscbS2QX6zA6au3EB7grrdzazQCh8+nYfeJZFxPyUelWoOOzjYYGNgRDw/qhnb2lnp7LyIiIiLSzdjI7vjtWCJu5ZVh76lkPDCwq7FDIiKie4hJqlqCt7EXSxBR2zK8nwe2HojH6ZhbyC+q4HdxBIDLMBIR1clcJsV9/T0AAL+f1N9SjAXFCrz1n2P4bNM5RN/IhVKlgRDAzexS/PjHdbzw8X4cv5yut/cjIiIiIt1YWsgwcYQ3AGDz3lhUKFVGjoiIiO4lJrnqzrJeXnxWGRHdWxc3e/h4toNGI7D/TKqxwyETwckyIqJ6jArzBACcu3YLWfllTT5fXlEF3vjiT1yKz4GF3AxPjfbFqgXD8c0792P+1H7o1skBpeWVWPLNaew5kdTk9yMiIiKixhk1wAsuTtbIK1Jg9/EkY4dDRER3kVtYjqy8MkglgHcXTpYRUcNUf++391QyhBBGjoZMASfLiIjq0bGDLQJ7OEMjgH2nUpp0rkqVGh+sP4Wb2SXo0M4Kn78ciSdH+qCzix2c7C0xOKgTlr40BGMGekEI4IstF3HySoaeMiEiIiIiXZjLpJhwX9XdZdsPxkNZqTZyREREVJ9ryVVLMHq628Pa0tzI0RBRSzGoT0dYys1wM7sUVxPzjB0OmQBOlhER3UX1VSZ7TiSjUqVp1DmEEFi19RJiU/Jha2WO9/8xEB6udrX2MzOT4oVxgRgdXjVhtnzzeeQWljcpfiIiIiJqnOH9PODsYIm8IgX+ON20C6eIiMhwriVVfcnN55URkS6sLc0xOKgTAP0+goVaLk6WERHdxcDAjmhnZ4G8ogocvXizUec4dP4m9p5KgVQCzJvSDx2dbevdVyKRYOZj/ujWyQHFZZVYuukcNBreCk5ERETU3MxlUowf3hMAsGX/dajUjbtwioiIDCsmsfp5ZZwsIyLdVF8kf/RSOkrLK40cDRkbJ8uIiO7CXCbFgxFdAQA/H7mh8xrG+cUVWLP9EgDgyZE+CPF1acB7mmHelL6wkJvhUnwODp1P0z1wIiIiImqykWGecLSzQFZ+OQ6eZU1GRGRqFJVqJNwsAMDJMiLSnY9nO3i42kKhVOPgOdZ6bR0ny4iI7mF0uBfkMiniUwt0XsP4P9svo7isEt06OuCJEd4NPq6zix0m/rX/ht3XUKniczKIiIiImpuFuRnGRnYHAPz4RxzUvOOfiMikxKcWQKUWaGdnAVcna2OHQ0QtjEQiwehwLwDAr8cSdb5InloXTpYREd2Dg60Fhvb1AAB8vze2wccdvZSOoxfTIZVKMHdiEGRmug25Dw/uBid7S2TlleG3Y0k6HUtERERE+jE63At21uZIzynFsYvpxg6HiIhuc/vzyiQSiZGjIaKWaHi/LrCQmyElsxjRN3KNHQ4ZESfLiIga4In7ekJmJsGFuGycu5Z1z/2LSpVYva1q+cXHh/dE986OOr+npVyGSaN8AACb98WhQqnS+RxERERE1DTWluZ4ZEjV3WXf7Y2Fms8uIyJqkGtJeXj/65N4fflhfLfnGpSV+l8xJSaJzysjoqaxtTLH0JDOAIBdRxONHA0ZEyfLiIgawK29DR6M6AYAWL8z+q5L8AghsGb7ZRQUK+DhaosnRzZ8+cU7jQztAlcnaxSVKrH/TGqjz0NEREREjffQoG6wszZH6q1i/HLkRqPOkV9UgXOxWdh3KgU/HYrHpj3X8MvhBBy9lI7cwnI9R0xEZFyX43OwaNVRnIzORGxKPjb9Hov5K4+guEypt/fQaIT2UQmcLCOipnhgYFcAwPHLGcgrqjByNGQsMmMHQETUUkwc6Y19p1OQlFGE344l4qFB3ercb/eJZBw6nwapBJg7MRjmMrNGv6eZmRSPDOmGtT9dwc+HEjB6gBekUi4tQURERNScbK3M8exDfoj64QI27rmGiD4d4dLu7s/GqVRpcOpqJo5dTMelhBwUFCvuun+IjwueebA3unVy0GfoRETNrkKhwtJNZ6FUaRDi44LQ3q7Y9HssEtIKsfirE/jgxYgm/Z1cLS2rGMVlSsjNzRq1mgsRUbVunRzQy8sJMUl52HMiWbvSE7UtTb6z7M8//8T48ePRp08fDB8+HOvWrdPpQXhXr16Fn58f0tLSmhoKEdE9ffvttxg+fLjOx125cgUD+gfDx7bq7q71O68iPrWg1n7XkvOwZvtlAMDUB3rD17PpV7eNDPWEjVXVczJOXc1s8vmIqHk0tkbauXMnHnzwQQQGBmLMmDHYvn17rX1+++03jB8/HsHBwYiMjMTChQuRk5NT7znnzp2LN954o0n5EBEZiy71W3JyMl566SUMGjQIffv2xaRJk3D8+HG9xDGifxf07uoEhVKNFZvP17scY6VKg93HkzDrw3348JvTOHzhJgqKFZBIgE4dbBDi44LI4M4YHe6FQX06ontnB0gkwLnYLLy2/BB+P5msl3iJiIzlp8MJyCmsgIuTNd6cFooHB3XDuH5mSDsahR2rXsTAQZENro0PHjyIxx9/HIGBgRgyZAjef/99lJWVAQCi/7qrzFYRjycnPtHg2piICABUKhWWLVuGyMhI9OnTB9F7l6E8PwW7jydBVU+dN3XqVPj4+NT7U5f9+/fX+xqZlibdWXbhwgX84x//wJgxY/DSSy/h7Nmz+OSTT6BWqzFz5sx7Hh8XF4eZM2dCpeJzeIjI8Hbt2oUPP/wQrq6uOh2nVCrxxhtvQKVSIbCnM0S7Djgfl4231xzDwmdCEdDDGUIIHD5/Eyt/vACVWoMB/m4YP6yHXuK2spBh9ABPbD0Qj58OJWCAv7tezktEhtPYGmnPnj14/fXX8fTTT2Pw4MHYt28f3njjDcjlcjz44IMAqsayV199FRMnTsQrr7yCnJwcLF++HM888wy2bdsGCwsL7fk0Gg2WLFmCPXv2YOzYsQbPm4hI33Sp3/Lz8zFlyhQ4OjrizTffhK2tLX788UdMnz4d33zzDUJDQ5sUi1QqwezH++DV5Ydx8XoOlm8+jzkTgmEuq7oGtUKhwoFzadjyRxyy8quWVWxnZ4GhfT0Q5ueG7p0cYGlR95/gmbml+OrnKzgZnYmoHy5AoxEYHe7VpHiJiIyhUqXGzj+rlqudOqYXLMzNcOHCBbzz5qsIHTgMyRWjUJab2KDaeP/+/Zg9ezYee+wxvPbaa0hISMDSpUuRn5+Pzz77DFdv5KLo5gXEnd/UoNqYiOh2H374IbZs2YLXXnsNnTp1wtdfr8fZk2thJn8Jp6IzMTCwY61j3nnnHZSUlNTYlpKSggULFmDChAm19j958iRee+01g+VA+tWkybKoqCj06tULn3zyCQBgyJAhUKlUWL16NZ5++mlYWlrWeZxSqcSGDRuwYsUKfmgRkcHl5uZi+fLl2Lx5MxwdHXU+ftmyZSguLgYASCQSvPFMf7z1n2OISynAm6uOontnB5RVqJCRUwoA6NPTGa9MCoFEor/lEh8e3A0/HUpA9I1cJKYXomtHLs9DZMoaWyMtXboUo0ePxptvvgkAGDx4MAoLC7F8+XLtZNnq1asRGRmJxYsXa4/r2rUrJkyYgAMHDmD06NEAgGvXruH999/H5cuX630/IiJT1Zj67aeffkJ+fj62bNminVyLiIjAo48+inXr1jV5sgwAurjZ47XJIfjwf2dw4Gwa4lLy0b+3GwpKFDgVnYmyiqoLQdvZWeDx+3pi9AAvyM3vvdSYW3sbLJoWiv/uvIptB+OxatsldHKxRUB35ybHTETUnI5cSEdhiRLODpYY1Kfqi+bq2vjrNVH4fm8sNu6+BolEgy9XrbprbbxkyRLcf//9WLJkCQAgPDwcarUa3377LcrLy3HlRi7y4vcjuN+Ae9bGRES3y8jIwHfffYdFixZh8uTJAIBBgwYhYshw5MUfxK6jvnVOlvXoUfPCeLVajffffx++vr5YtGiRdntJSQnWrl2LtWvXws7OTntHLJm2Ri/DqFQqcfLkSYwcObLG9vvvvx+lpaU4e/ZsvccePnwYK1euxKxZs/D66683NgQiogZZvXo1/vzzT0RFRWHYsGE6HXvu3Dls2LABb7/9tnabtaU5/u+FCIwM7QKpBEhIK0RGTiks5GaYPMoH7z4fDmtLc73m0N7BCuEBVXeU7WjkQ+WJqHk0tkZKS0tDUlJSncclJycjKSkJGo0GERERta5Y69at6hmKKSkp2m0LFiyAWq3G5s2b0b59e32kRkTUbBpTv7m6uuLZZ5+tcReamZkZPD09a4yPTRUe0BFvTQ+Do60FbmaX4qdDCTh4Ng1lFSq4t7fB84/6Y+2ikXhkcPcGTZRVk0gkePah3hga0hkajcDSjWdRWl6pt7iJiJrD0YvpAIBRYZ6QmUlr1cYT7vNGmJ8bbFwDUF5WhkNHTtR5nqtXryIlJQVTpkypsf2ZZ57Bvn37UFwukJ1fCpsO3nh66lM19qmrNiYiut3x48ehUqlq/P0tl8tx37BhKMu+hkvxOUi9VXzP83z//feIjo7Ge++9B7lcrt2+ZcsW/PDDD3j77bdrjWNkuhp9Z1lqaioqKyvh5eVVY7unpycAIDExEREREXUeGxAQgP3798PR0RHbtm1rbAhERA3y5JNPYv78+TA3N8f+/fsbfFx5eTkWLlyIWbNm1Vpb2FIuw9yJwZg0yhdxqfmQy6To3bU9bKz0O0l2u4cHd8OfF9Nx6FwannmwNxxseWcukSlqbI2UkJAAAHc9zsvLq85nj+3btw8A0LNnT+22jz/+mOuiE1GL1Zj67YEHHsADDzxQY1thYSFOnz6NAQMG6DW+fr1csfqN+3D4wk2k3iqGvY0cvbycENDdGVJp41cXkEiqlnqMTclHRk4pvvn1Kl4c30ePkRMRGY6iUo0L17MBAAP+utjzztpYKpXglUkhSEy9hRQAX285jBHDh8DMrOb1/DExMQAACwsLzJo1C8ePH4elpSUeffRRzJs3D9GJuZBIpIgYPQUPjI6scWxdtTER0e0SEhJgY2ODDh061Nju69Md27cVQaNS4NdjiZg1NrDec5SWlmLFihV49NFHERhYc7/hw4dj4sSJsLKyQlRUlEFyIP1r9J1l1UuS2dra1thuY2MDALXW7rydq6tro5ZCIyJqjO7du8PcXPdJrM8++wzW1taYNWtWvft0aGeFiMCO6N/bzaATZQDQy8sJ3Ts7QKnS8MHvRCassTVS9XZdj0tJScFHH32EXr16ITLy7y8KOFFGRC1ZY+u322k0Grz11lsoKSnBc889p6fI/mZjZY4x4V6Y+VgAnhzpgz49OzRpoqyapYUMc54IAgDsOZHcoKuaiYhMweX4HCgr1XB2sISXuz2AumtjGytz/GvGIABAakYuvt4ZXetceXl5AIB//vOf6NGjB9asWYPnn38emzdvxsKFC3E5PgcA0LtrzRUU6quNiYhuV1xcXOtvb+Dvv781qgrsP5OKcoWq3nNs3boVRUVFdX5v2KVLF1hZWekvYGoWjZ4s02g0dz+xtNGnJiIyupMnT2Lz5s1YsmQJZLImPd5RbyQSCR4eVLWcxK/HkqBW330cJiLjaGyN1JjjEhIS8PTTT0Mmk2HFihWsv4iI/lJZWYl58+Zhz549WLRoUa2rfU1dQA9nhPm5QaMR+N+vV40dDhFRg5y6mgkA6N/bTfsM7/pqXA+3qsk0iUSCXw7fwL5TNZdMrKysWoZ25MiRmDdvHgYMGIDnn38e//znP7Fz5078eeoKACDYx0V7DGtjImooIcRdX3d1skFZhQqHzqXVu8/GjRsxfPhwdO3aVd/hkZE0+lPDzs4OQNXthrer76poIqKWorS0FAsXLsTzzz+PHj16QKVSaQt8jUYDlar+q0oMbXBQJzjYypFTUI4T0ZlGi4OI6tfYGknX406ePIlJkyYBAL755ht06dKliZETEbUORUVFmDFjBn799Ve89dZbeOqpp+59kAl65sHekEolOHElE1cTc40dDhHRXQkhcPrqLQBAqJ+bdvu9atzQgKolx7/YchGxyXna16vv7hg6dGiN4wYPHgwAyEq/AQu5Gfy7Vd1ZxtqYiHRha2tba1wC/h6bHhziCwDYdTSxzom1a9euISkpCQ8//LBhA6Vm1ejJsi5dusDMzAzJyTWXAqt+eGb37t2bFhkRkZFcuXIFN2/exBdffAE/Pz/4+flpH/i5aNEi+Pn5GS02ubkZ7h/gBQDYceSG0eIgovo1tkaqvhrtzuOq/337cTt37sSMGTPg6uqKzZs3s+4iIvpLZmYmJk6ciPPnz2Pp0qUt+oHqHq52GBla9WXvj39cN3I0RER3l5RRhJyCcsjNzRDQw1m7/V618cSHwhHm5waVWoMP/nsK+cUVAP5+jq9SqaxxXPUdZxKpOQK6O0NubsbamIh01q1bN5SUlGiXfK2WnJyMTp06YUxET8jNzZCUUYSYpLxaxx88eBBWVla1JvSpZWv0ZJmFhQX69euHvXv31phd3bNnD+zs7FrcMhdERNX8/PywZcuWGj+rVq0CULVe+pYtW4wa3wMDvSCVShB9IxcJaQVGjYWIamtsjeTp6YnOnTtjz549Nbb//vvv8PLyQufOnQEAhw4dwvz58xEcHIzvvvsOrq6uhkuGiKgFKSkpwTPPPIOsrCysX78eY8aMMXZITTZ+WE9IJcCZmFtIyigydjhERPWqXoIxqGcHWJibabffqzbu06cPXp0cAg9XW+QVKfDphrNQawT69esHa2tr7Nq1q8b77N+/HxKJFJbtPDHA3521MRE1ysCBAwEAu3fv1m5TKpU4ePAgIiIiYGstR2RwJwBVd5fd6cKFC+jduzcsLS2bJ2BqFk16EM8LL7yAadOm4aWXXsL48eNx/vx5rFu3Dq+99pr2AXYlJSWIj49Hly5d4OTkpJegiYj0LSUlBXl5eQgKCoKtrS0CAgJqvJ6WVrVGcadOnWq91tzaO1hhUJ+OOHz+JjbsvoZ3nhtg1HiIqLbG1kizZ8/GwoUL4ejoiOHDh+OPP/7Ab7/9hs8//xwAoFAosGjRItjY2OAf//gH4uPja7yvm5sb3NzcQETUFtxevwHAihUrkJSUhDlz5kAmk+HChQvafeVyOXr37m2cQJvA3dkG4YEdcfRiOrYfjMcrk0KMHRIRUZ2ql2Ds37v2ZFVDauM543vhtY+341x0Cb773QlTRvfC3Llz8eGHH8Le3h6jRo3CuXPnsHbtWjh2HQS5lR2Ce7bDuEefYm1MRDrr1KkTxo4diyVLlkChUMDLywvr169HUVERnnvuOQDAAwO7YteB89h3MAXPPeqPdnZ/T4zFxcVh0KBBxgqfDKRJk2Xh4eGIiorCihUrMHv2bLi6umL+/PmYPn26dp/o6Gg8/fTTWLJkCcaNG9fkgImIDOHLL7/E9u3bERsba+xQGmTy/b7482I6zsTcwuWEHAR0d773QUTUbBpbI40bNw5KpRJff/01tm7dCg8PD3z00Ud44IEHAADnzp1DdnY2ANQ4V7V//vOfmDNnTjNkSERkfHfWb7///jsAICoqClFRUTX27dSpE/bv39/sMerDuKE9cPRiOg6dS8OU0b3QoZ2VsUMiIqqhoFiBuJR8AHVPljWkNi7KSUXCwRVw7TMBm/faopeXE6ZNmwZ7e3usX78eP/74I1xcXBAxaiLSJQHo08MZCXHRrI2JqNEWL14Me3t7rF27FmVlZfDz88P69evh6Vn1LMUeHo5QpR9GWuxx7D42EpPu99Uem5ubC3t7e2OFTgYiEXU9oY6IiEzel1sv4rdjSfDu4ohP5w6BRCIxdkhEREREZACLVh3FpfgcPBbZHTMe8Td2OERENfxxOgXLvj+P7p0dsOyVoU0615dbLuK340mws5Zj2auRcGlnrX2tXKHCtH//jtLySrw1PQyhfrxrjIgM6/D5NHyy4SzsrOX4+l8jYWnRpHuPyMQ1+pllRERkXJNG+cBSboa4lAL8djzJ2OEQERERkYGMG9YDALDnRBJKypRGjoaIqCbtEoy9mj559dyj/uje2QHFZUp8/L8zqFRptK9t3huL0vJKdOpgg369+GwyIjK8iMCOcG9vg+IyJfacTDZ2OGRgnCwjImqh2tlZYuoDvQAAX++IRnxagXEDIiIiIiKDCPFxgZe7PcoVauys4yHzRETGUqnS4FxsFoC6l2DUldzcDG883R82ljLEpuTjg/+eQmGJAscvZ+CnQwkAgOkP+0Mq5coqRGR4ZmZS7UVLPx2MrzGBT60PJ8uIiFqwhyK6Idi7AxRKNd5bewLxqQXGDomIiIiI9EwikeCJ+3oCAH45fAMVCpWRIyIiqhJ9IwflChUc7SzQo7OjXs7p1t4G86b2g1wmxZmYW5jyzm588N9TUGsEhoZ05vKLRNSs7uvvASd7C+QUVuD3E0k6H1+hVCH1VjHKKir1HxzpFSfLiIhaMKlUggVP90e3Tg4oKFFg/soj+O/OaKTeKgYfSUlERETUenAZICIyRX8vweiq17u9+vq6YsnsQeje2QEAYCaVYEy4F156Mlhv70FE1BDmMjNMGOEDAPh+bxzKG3jRUl5RBT7bdBZPLvoVL368H5Pe+g3Lvz+PknJOmpkqieC3qURELV5ZRSU+3XhW+4cKAO2Vfd07O6B7J0f07uoEB1sLI0ZJRERERE2x50QSVv54Ee0dLLH2zZEwl/H6VyIyHiEEZi35Axm5pXjz2f4ID+hokPcoKFbA3NwMtlbmej8/EVFDqNQavPjxfmTklGLyKB9Mut/3rvsnpBXg3bUnUFCiAABYyM2gUKoBAB2dbfB/L0TA2dHK4HGTbjhZRkTUSgghcOJKJvadSsHZa7eg1tQc3mVmEgwM6Iixw3robXkMIiIiImo+lSo1nvu/fcgrqsCcCUEYFeZp7JCIqA1LTC/E3M8OwlwmxcbFY2BlITN2SEREBvPnxZv46H9nYCk3wxfzh8OlnXWd+8WnFeCt1cdQUl4JL3d7zJkQBO8u7RCTmIdPNp5Bdn45OrvY4rOXhsDakhcBmBJOlhERtUIVShWSMooQn1qA+LQCxKUUIPVWMQBAIgFGhnpi6phecLTjnWZERERELclPh+Kx7pdouDhZY9X84ZCbmxk7JCJqozbsjsHmvXEI83PDv6aHGTscIiKDEkJgwco/EZOUh6CeHfDuzHCY3bH8bFxKPt5Zcxwl5ZXw8WyHxTPDa0yIZeWVYcHKI8gprMDgoE6YN6UvJBL9LWFLTcM1G4iIWiFLuQy+nk54aFA3vPxkCL6cPxyfvxyJIcGdIATw+8lkzPpwH34+nAC1WmPscImIiIiogUYP8EJ7B0tk5ZXh58MJxg6HiNqwY5fSAQARffS//CIRkamRSCSYOzEIcpkUF65n4+sdV3D7fUiXE3Lwr7/uKOvl5VRrogwAXJysseCZ/jCTSnDkwk38djypmbOgu+GdZUREbUxMYh7W/HQJ8WmFAIAubnZ4cqQPBgZ2rHVFTF3Uag2UKg2EELCykPEKGCIiIqJmdvBsKj7bdA6WcjOsfuM+tHfgMy+IqHmlZBZh9icHIDOTYMN7Y2DD54kRURtx6FwaPt14FgAwwN8NQ/t6ICYxDzv+vAGNRiCwhzP+NT3srkvTVq8UYC6TYunLkfByt2+u8OkuOFlGRNQGqTUC+04l45tdMSguUwIAOrSzQri/O3p1dUIHRyuo1AKFJQrczC5BWlYJMnJKkZ1fhtyiClR/clhbytDZxRZ9fV0R0acjPN344U5ERERkaEIIzI86gmvJ+RgY6I43nu7PC5iIqFl9vzcWG3dfQ79ernjnuQHGDoeIqFntPp6EVVsvQnPHzMqQ4E6YOzEYFvdYJlsIgcXrTuJMzC14uNph6ctDYCnncx+NjZNlRERtWEmZEjuO3MAvR26gpLyyyecL8XXBkyN80Kurkx6iIyIiIqL6JKQV4LXlh6HWCLwwPhAPDOxq7JCIqI0QQuCFj/bjZnYJXpoYhBGhnsYOiYio2SVlFGH7wXgkphfCrb0NRoV5oq+vS4MvYCosUWDOpweQX6zA6HAvzH68j4EjpnvhZBkREaFCqcL52GycvpqJtKwSZBeUQy6TwtbaHB072KKziy06OtvC1ckaHRytYGUpgxBAdn4ZrqcW4PjlDJy+mqm9omZ4Pw9Me8gPjnYWxk2MiIiIqBXbduA61u+8CqlUgjef6Y8wf3djh9RkOQXl2HHkBk5GZ+BWXjmsLMzg4+mE0QM8EernxjvoiEzApfhsLFp1DFYWZvjv2/fXeiYPERE1zIW4LLy95jiEAF5/qi8iQzobO6Q2jZNlRESkF5m5pfhhXxz2nU6BEIC9jRz/fCII4QEt/0sbIiIiIlMkhMDn353DgbNpkEolmDqmFx6L7A6ZmdTYoelMCIEdf97AN7tioKxU17lPiI8LXp4UjHZ2ls0cHRHd7v2vT+JkdCbGDPTCi+N5JwQRUVN8s+sqtuy/DpmZFO/NHIDAHh2MHVKbxckyIiLSq7iUfET9cAFJGUUAgPv6e2DmYwG82pCIiIjIANRqDVb8cAH7z6QCANo7WGJgYEf08nSCk4Ml2jtYwspCBksLGeQyqUnemVWhUGHljxdx6HwaAKCXlxMei+yOHp0dUVSqxJ8Xb2LHkRtQqjRwtLPAomdD4evFZb+JjCE+rQCvfH4IUgmwct5weLjaGTskIqIWTa0R+Pjb0zh2KQNWFjK8NSMMAd2djR1Wm9QiJstyc3ONHQIRtQDt27c3dgj0l0qVGht3X8O2g/EQAnBpZ4WXJ4WYxIe9EAIqtQYAIDMzzS+MiIyB9RYRGQPrN/0QQmDfqRT879cYFJQo6t1Pbm6GLq628HJ3QI/ODujdrT283O2NWg9l5JTig/+eQlJGEcykEkx/2A8PD+5WK6bkzCJ8uuEskjKKYCE3w6JnQxHs42KkqIl0J4TArbwy2FqZw8bKXG/9TlGpRkmZEhVKNSoUKlQo1ShXqFBYokB6TinSs0uQkVuKzNwyaDQayMzM4O5sja4dHdDX1xXBPh1gKZc16L3UGoGFX/yJmKQ8DA3pjNee6quXHJob616itqUl1JvKSjXeXXsClxNyIJVK8Mjgbngwoivc2tsAqBrrcwvLkVNQjpKySsjNzeBoZwEvd/sWuaKAqWoRk2WdOnUydghE1ALcvHnT2CHQHaJv5OLz787hVl4ZJBLgscgemDrGF+Yys2Z5/5IyJVJuFSMlsxhJGUVITC9EUkYRyipUAABrSxl6d22PiEB3DArq1OA/EolaI9ZbRGQMrN/0S1mpxoW4bJy4koH0nFLkFJQjv6gCSpWm3mOc7C3R19cFIb4uCPJ2ga1V860GcCbmFj7deBal5ZVwtLPAgqn94H+Xi6sqFCos+eY0zsVmQWYmxbwpfTEwsGOzxUvUFF/viMb2g/EAABsrc3h7OMKve3v083VFt04ODZ48U1SqcepKJg6eS8P11HzkF9c/Qd4QcpkUQd4uCA9wQ5i/O+ys5fXuu2F3DDbvjYOVhRlWvj4cLk7WTXpvY2HdS9S2tJR6s0Kpwsof/r7THqj63kqtEVAo616iWi6Twr+HM4aGdMYAf3dYWfB7rabgZBkRtRot5cOvrSmrqMRXP1/B3lMpAABPNzu8OrkvunVyaNJ5s/LKcDUpDzduFqKwRIGiUiVKypQoV6hQrlChrEKFkvLKBp/P0c4CE0d4Y3S4F6/KoTaJ9RYRGQPrt+ahVmugqFQjv1iB5Iwi3EgvxPWUAly5kVvj+WBSCdC9syP69OyAPj2d4evpBEsDfOmiqFTjf7uu4pcjNwAAPp7tsPCZ/mjvYHXPYytVany68SyOXcqAVALMmRCMEaFd9B4jkb4dPJuKtT9fQVGpstZrzo5WGBjgjvAAd/Tq2h5m0poTZ2qNwNXEXBw4k4qjl9K1F/9Vk0olsJKbwUIug5WFGSwtZLCzksPd2QYdO9igo7Mt3NpbQ25uhnKFCunZpbiamIsT0ZnIyivTnsdMKkEf7w4YGOCO3l3bo2MHW5hJJcgvrsAPe+Ow82giAOCliS2737HuJWpbWlq9eSbmFrYfjEf0jVyoNX9P3VjIzeDsYAU7a3NUqjXIzC1D6W3fe1nIzRAe4I4R/bogoIczpFKupKQrTpYRUavR0j782pqTVzIQ9eMFFJYoIZUADwzsiqdG+8L2Llcu3qlSpcbxyxnYfTwZlxNyGnSMs6MVPFxs4dXRAV072sPL3R4d2llDAuBWXhlOXc3E3lMp2j8Su3VywJwJQejR2bERWRK1XKy3iMgYWL8Zl7JSjegbuTgXm4Wz124h9VZJjdelEqCzqx16dHZE984O6OhsC3dnG7i0s4a5TPeLi1RqDQ6eTcMP++KQkVsKAHgwoitmPOKv0/nUag2+2HJRezHW84/645Eh3XWOh8gYlJVqpN4qxrWkPJyPy8bF69mouO2OAUdbCwT5dIBLO2vt0o0Xr2ejsOTvSbYO7awwrK8HQnu7omMHW9g2cllHIQSSMopw4komjl1K1z53upq5TAobS/May7tOGeOLiSN8GpG56WDdS9S2tNR6s0KpQnZ+OWRmUtjZyGFjKasx1ms0AqlZxTh6MR0Hz6UhI6dU+5qzoxWG9/PA8H4e6NTB1hjht0icLCOiVqOlfvi1JQXFCqzefglHL6YDAOxt5Hh8eE+MDve6663i6Tkl2HM8GX+cSdH+kSiVAD08HOHt0Q7Ojlawt5HD1tocVhYy7Y+zoxWsLe+9lFClSoO9p5Lx7a8xKCmvhFQqwdjI7ph0vy8szJtnyUgiY2O9RUTGwPrNtOQUlONSfDYuXs/BxevZyC2sqHM/qaTqS5j2DlU1WFUdJofcXApzmRTmZlLIZFKYy8wgk0qQV1SBpIwinI/NQulfd8S0s7PA3InB6NfLtVGxCiGw7pdo/Hw4AQDwxH09MWV0L15FTS2OolKNC7FZOHY5A6eiM+tdHcPGUoaBgR0xrJ8H/Lq2N8jvelpWMY5eSse5a1lIuFlYY9kvny7tMOl+H/T1bVyfNSWse4nalrZQbwohEJuSj/2nU3H4fJq23gIA7y6OGBrigcFBneBoZ2HEKE1fi5gs44M3iaghWsIDO6nKxbhs/Oeny0i9VQygas3+cH939O3lgk4dbGFnLcetvDLEpxXg6MV0xCTlaY91srfEyLAuGBXmCZd2+l0jP7+4Amt/uoIjF6oKKXdnG8x5IggBPep/dgZRa8F6i4iMgfWbacstLEdCWiHi0wqQmF6IzNwyZOSW1vvcjIZoZ2eBxyK7Y8zArk1+roYQApv3xWHj7msAgH69XPHKpBDY2zR85QIiU6JSa3A5PgfXUwuQW1gOiUSC9g6W8O7SDn7d2jfrcvFqjUB2fhnKFSo42VvCwbb1fMHKupeobWlr9aayUo2T0Zn443QKzsdlQ/PXUo5SqQQhPi4Y0b8LQv3cGrVKQGvXIibLiIio9VGpNfjjdCq2Hrhe41bxukgkQLCPC0YP8EJob1eYGfiPxJNXMrBq2yXt1dT3D/DEsw/5NesD74mIiIhMkRAC+cUKZOSUouCv58YWlSpQUlaJSpXmrx+19r9Vag0c7Szg7myDPj07wNujnd7viNl/JhVf/HgBSpUGjrYWmPGoPyKDOzVqWToiIiKi1iK/uAJHLtzEwbNpuJ5aoN3uYCvHsL4eGBXmCQ9XO+MFaGI4WUZEREal1ghcvZGLY5fSEZeaj4ycUpRVqNDO3hJd3OwQ4uOCiMCOcHa89wPf9am0vBLf7LqK344nAQCc7C0wflhPDO/fxSQmzcoqKpGeU4qCYgU83ezRoV3z/v9DREREZEoS0grw2aZz2pULvNztMW5YD4QHuMNS3rQ72IiIiIhaurSsYuw/k4o/Tqcgr+jvZ1H27uqEUWGeCA9wb9CjTFozTpYRERHdxZWEHKz88QJuZlfd/SaXSRHQwxmBPTrAy71qksreRg5bK/N6r5K+2yft3T6ES8srcSuvFJm5ZcjMLUVGTinSc0qRnl2C/OK/CxuXdlZY969RjUmPiIiIqNWoVKmx9UA8th24jnJF1VKRlnIz9OnZAT09HNHDwxEdHK3gYGsBW2s5pBJAIpGgUqVBWUUlSssrUVpRibJyFcoUlSirUKGsQoVyhQqBPZzh6+Vk5AyJiIiImkat1uDstSz8fjIZp2NuaZdplJlJ4N/NGSG+Lujp4Qivjg6NulhcrRFQVqqhUKqhqFRDqf3RQPnX6gPV2ysUKpQr1KhQqlChVKN/b1cEdDfeo1A4WUZERHQPyko19p1Owa6jiUjJLDZ2OFoOtnI4O1phYEBHTBjhbexwiIiIiExCSZkSO48mYt+pFNzKK7vrvhLJ3S9sqtbR2Qb/WThCTxESERERGV9uYTn+OF11t1l6HY9IcbS1gJ2NOWyt5DCXSSGVSLQXiisq/5rkUqihUKqg+GuCTKnSNDqebh0dsPy1oY0+vqk4WUZERNRAQgik3CrG2ZhbiEstQEpmEfKKFCgtrzTYezrZW8DVyQauTtbo6GwD9w626Ohsg44dbE1iOUgiIiIiUyWEwPXUAlxNzMP11HzcuFmI/OL6azcrCxlsrMxhYymDtaU5rCxlsLKQwdpChvAAd/Tv7dbMGRARERE1j5vZJTgTcwuXrucgMaMQ2fnlTT6n3NwMcpkUcnMzWJibwdxcqv23XGYGSwszWFnIYGkhg5VchvBAd/h6Gu9Ofk6WERERNZFarUFphQp3+0i92wPm63upupggIiIiIv1RqTUo+6t202gEzGVSWFmaw6yeJbWJiIiI2pqS8kpk55ehpKwSxWVKVKo00AgBIQSEACzkZrCUy/7637//28LcDBbyqsmw+h5XYqo4WUZERERERERERERERERtltTYARAREREREREREREREREZCyfLiIiIiIiIiIiIiIiIqM3iZBkRERERERERERERERG1WZwsIyIiIiIiIiIiIiIiojaLk2VERERERERERERERETUZnGyjIiIiIiIiIiIiIiIiNosTpYRERERERERERERERFRm8XJMiIiIiIiIiIiIiIiImqzOFlGREREREREREREREREbRYny4iIiIiIiIiIiIiIiKjN4mQZERERERERERERERERtVmcLCMiIiIiIiIiIiIiIqI2i5NlRERERERERERERERE1GZxsoyIiIiIiIiIiIiIiIjaLJm+TvTf//4XhYWF+jodERERmQAHBwc8++yzxg6DwFqLiIiotWK9ZTpYbxEREbVODam39H5nmRACFRUVEELo+9TUBGwX08R2MV1sG9PEdiFqurbUj5hr68RcW5+2kifAXFurtpQrmb62+PvY1nJmvq0b823dmK9pkwg9R5qRkYE1a9Zg5syZcHd31+epqQnYLqaJ7WK62Damie1C1HRtqR8x19aJubY+bSVPgLm2Vm0pVzJ9bfH3sa3lzHxbN+bbujFf08ZnlhEREREREREREREREVGbxckyIiIiIiIiIiIiIiIiarP0Pllma2uLyMhI2Nra6vvU1ARsF9PEdjFdbBvTxHYharq21I+Ya+vEXFuftpInwFxbq7aUK5m+tvj72NZyZr6tG/Nt3ZivadP7M8uIiIiIiIiIiIiIiIiIWgouw0hERERERERERERERERtFifLiIiIiIiIiIiIiIiIqM3iZBkRERERERERERERERG1WTpPlmk0GqxYsQKDBw9GUFAQnn/+eaSmpta7f35+Pl577TX0798foaGheO+991BeXt6koKk2Xdvll19+gY+PT62ftLS0Zoy6bfnPf/6DqVOn3nUf9hfjaEjbsM80j4KCArz99tsYMmQIQkJCMGnSJJw5c6be/dPS0jBr1iyEhIRg0KBBWLZsGdRqdTNGTGR8hqjNfvvtNzzwwAMIDAzEY489huPHjxs6jQbRNdfr169j5syZCAsLQ3h4OObOnYv09HTt62q1GoGBgbXG9qioqOZI564MUduZYrvqkmdUVFSdOfr4+GDhwoXa/aZNm1br9Xt9zjc3fdWFptimd2pIri25r95OXzVla2jXltxfDVGPbty4Effddx8CAwMxefJkXL161dBpUCuia01QWVmJzz77TLv/lClTEBMTU2Of48ePY9y4cejTpw9Gjx6NXbt2GTqNBjNEvlu3bsXDDz+MoKAgjBo1CmvWrDGZvxsNkW81IQRmzJhh9HH1TobIOTExETNnzkRwcDAiIiKwePFik/k+zRD5Hjt2DOPHj0dQUBBGjBiBdevWGTqNBjNEfd9axqyG5ttaxqyG5lvNJMYsoaOoqCgRFhYmDhw4IGJiYsT06dPFqFGjhEKhqHP/KVOmiPHjx4srV66IY8eOiWHDhon58+fr+rZ0D7q2y8cffyymTJkisrKyavyoVKpmjrxt2LBhg/D19RVTpky5637sL82voW3DPtM8pk2bJh566CFx+vRpcePGDfHee++JwMBAkZCQUGtfpVIpRo0aJWbOnCliY2PF3r17RWhoqFi+fLkRIicyHn3XZsePHxd+fn7im2++EfHx8eLDDz8U/v7+Ij4+vrlSqpcuuebl5YmIiAgxZ84cERsbKy5fviyeeuopMWbMGFFRUSGEECI+Pl54e3uLmJiYGmN7SUlJc6dWi75rO1NtV13yLCkpqZXfRx99JIKCgsS1a9e0+4WHh4tNmzbV2C8/P78Zs7o7fdWFptqmt2tIri29r1bTV03ZWtq1JfdXfdej27ZtE4GBgeLnn38W169fF/PmzROhoaEiNze3OdOiFkzXmuDNN98UAwcOFIcPHxbx8fFizpw5IiIiQhQVFQkhqsbUgIAAsXTpUhEfHy+++uor0bt3b3Hs2LHmTKte+s73559/Fn5+fuL7778XycnJYteuXSIkJERERUU1Z1r10ne+t1u/fr3w9va+52dTc9N3znl5eWLgwIHihRdeENevXxdHjx4VgwYNEu+8804zZlU/feebkJAg/P39RVRUlEhJSRG7du0SgYGBYsOGDc2ZVr30Xd+3pjGrIfm2pjGrofVgNVMYs3SaLFMoFCI4OFhs3LhRu62wsFAEBgaKHTt21Nr/3Llzwtvbu0Zhf+TIEeHj4yMyMzObEDbdTtd2EUKI5557Tvz73/9urhDbrMzMTDFr1iwRFBQkRo8efdfOzv7SvHRpGyHYZ5pDUlKS8Pb2FmfOnNFu02g0YsSIEWLZsmW19t+xY4fw9/cXBQUF2m3ff/+9CAkJqbfoJGptDFGbTZ8+Xbz00ks1jps4caJ46623DJNEA+ma6w8//CCCg4NFeXm5dlt6errw9vbW/mFV/YeHqTFEbWeK7dqYPG8XHR0t/Pz8xLZt27TbcnJyhLe3t4iOjjZIzE2h77rQFNu0mi65tuS+KoT+a8rW0q53ain91RD16KhRo8THH3+sfb2yslJERkaK1atXGzATai10/axMSUkRPj4+4sCBAzX2HzZsmHZMfeutt8Tjjz9e47hXX31VTJ8+3TBJ6MAQ+T755JNi0aJFNY5buXKliIyMNEgOujBEvtWuXbsm+vXrJyZMmGBSk2WGyHnFihViyJAh2otshKiqL8aOHSs0Go3hkmkAQ+S7fv16ERoaWuO42bNni1mzZhkmCR0Yor5vTWPWnerKtzWNWXeqK99qpjJm6bQM47Vr11BaWorw8HDtNnt7e/Tu3RunT5+utf+ZM2fQoUMHdO/eXbstNDQUEokEZ8+ebcL9cHQ7XdsFAGJjY2u0CxlGdHQ0zM3N8csvv6BPnz533Zf9pXnp0jYA+0xzaNeuHdasWYOAgADtNolEAolEgqKiolr7nzlzBn5+fnBwcNBuGzBgAEpKSupdhoKotdF3babRaHDu3Lka5wOAsLCwemuK5qJrruHh4fjyyy9haWmp3SaVVpW+1WOKqY7t+q7tTLVdG5Pn7RYvXox+/fph7Nix2m2xsbGQSCTo2rWrQWJuCn3WhabaptV0ybUl91VAvzVla2rXO7WU/qrvejQ3NxdJSUk12lQmk6Ffv34m0aZk+nT9rDx69Cjs7OwwZMiQGvvv379fe44zZ87UGmcGDBiAs2fPQghhoEwaxhD5vv7665gxY0aN46RSKQoLCw2URcMZIl8AUCgUeP311zF37lyTGmMBw+T8559/YuTIkbCwsNDu88QTT2Dbtm2QSCQGzObeDJFv+/btUVBQgJ07d0IIgdjYWJw9e1bnz2ZDMER935rGrDvVlW9rGrPuVFe+gGmNWTpNlmVmZgIA3N3da2x3cXHRvna7W7du1dpXLpfD0dERGRkZusZK9dC1XQoLC3Hr1i2cOXMGDz/8MAYNGoQXX3wRiYmJzRJvWzJ8+HBERUXBw8PjnvuyvzQvXdqGfaZ52NvbIzIyEnK5XLttz549SE5OxuDBg2vtn5mZCTc3txrbXFxcAIB9htoMfddmRUVFKCsrq7Nv1XW+5qRrrp07d8aAAQNqbFuzZg0sLS3Rv39/AEBcXBxUKhVmzJiBiIgIjBs3Dj///LOBMmg4fdd2ptquuuZ5uwMHDuD8+fNYsGBBje1xcXGws7PD4sWLMWTIEIwePRrLli2DUqnUb/CNoM+60FTbtJouubbkvgrot6ZsTe16u5bUX/VdjzZlnCMCdP+sTExMhIeHB37//XeMGzcOEREReP7555GQkFDjnHX93paXlyM/P98AWTScIfLt27dvjS9fi4uL8d1339XZp5ubIfIFgE8++QQuLi6YMmWK4YJvJEPknJiYCBcXFyxZsgRDhw7FyJEj8fHHH0OhUBg2mQYwRL5jxozBE088gXnz5sHPzw+PPPIIIiIi8I9//MOwyTSAIer71jRm3a6+fFvTmHW7+vIFTGvM0mmyrPrBiLcXjgBgYWFR5wBUXl5ea9+77U+No2u7XL9+HUDVQ/OWLFmCZcuWQaFQYPLkycjJyTF8wFQn9hfTxT5jHOfOncPChQsxatQoDB06tNbrFRUVdY57ANhnqM3Qd21WUVGh0/mak6653unbb7/Fhg0b8Prrr8PJyQlA1fheUFCAqVOnYt26dbj//vuxcOFCbNmyRf8J6EDftZ2ptmtT2nT9+vUYNmwYevXqVWN7XFwcFAoFAgMD8dVXX+GFF17Ajz/+iH/961/6Dd7AWnJfbaqW1Fd11VL7alO15P7a1Hq0qZ9dRLr+DpWUlCA5ORlffvklXn31VaxatQoymQyTJ09Gbm4ugLp/b6v/beyLSwyR7+1KS0vx4osvQqFQYP78+YZJQgeGyPfw4cPYsWMHPvjgA6PfVVUXQ+RcUlKCtWvXQqFQYOXKlZg3bx527NhhEp8nhsg3NzcXN2/exNy5c7Flyxb83//9Hw4dOoSoqCjDJ3QPhqjvW9OYdbv68r1dSx+zbldfvqY2Zsl02bl6aQylUlljmQyFQgErK6s696/rl1ahUMDa2lrXWKkeurZLv379cPz4cbRr1077S7hy5UoMHToU27Ztw8yZM5sncKqB/cV0sc80v3379uH1119HSEgIPv300zr3qavPVH84s89QW6Hv2qz6C766+lZd52tOuuZaTQiB5cuXY9WqVXjhhRcwdepU7Ws7d+6EWq2GjY0NAMDX1xfp6elYt24dHn/8cQNlcm/6ru2eeOIJ7fluZ+x2bWybpqen4+TJk1izZk2t1xYvXowFCxZol0Tz9vaGubk5XnnlFcyfPx/Ozs56zsIwWnJfbayW2Fd11VL7alO05P6qj3r09nHuzn1aaptS89L1s1Imk6GkpASff/65dsnXzz//HJGRkdi+fTuee+45WFhY1PqdrP63sX8vDZFvtezsbMyaNQtpaWlYt24dOnfubOBs7k3f+Y4bNw5vvvkm3n33Xbi6ujZPEjoyRBvLZDJ07doV7777LgDA398farUaL7/8Mt544w20b9/e8InVwxD5Llq0CO7u7njhhRcAAL1794YQAu+++y6mTJmivdjIGAxR37emMava3fKt1hrGrGr15ZuXl2dyY5ZOd5ZV32KXlZVVY3tWVladCbm5udXaV6lUoqCgQLs0ATWdru0CAE5OTjVma62srNC5c2fcunXLcIHSXbG/mDb2meazYcMGzJkzB8OGDcPq1atrrDt+u7r6TPW/TeVDlsjQ9F2bOTo6wtraWqeaork0pt6prKzEvHnzsHr1aixcuBAvv/xyjdctLS21X75X8/b2NvrSWPqu7Uy1XRuTJ1D1BbaTkxMiIiJqvSaTyWo8OwgAevbsCQBGb1ddtOS+2hgtta82Rkvsq03RUvurvurRxo5zRNUaU+vJZLIaz0a0tLSEh4cH0tLStOes63zW1taws7PTdwo6MUS+AJCQkIAJEyYgNzcXGzdurPFcQmPSd76HDh1CdnY23nzzTQQHByM4OBg7duzAmTNnEBwcjPT0dMMm1ACGaGM3Nzft50e16n/fvHlTr/HryhD5nj17ttbvcFBQEFQqVY3fe2MwRH3fmsasanfLF2g9Y1a1+vI1xTFLp8kyX19f2Nra4uTJk9ptRUVFuHr1qnY9+dv1798fmZmZSE5O1m47deoUgKr1N0k/dG2XzZs3IywsDGVlZdptJSUlSEpKQo8ePZolZqqN/cV0sc80n02bNuHf//43nnrqKSxdurTOJaiq9e/fH1evXkVJSYl224kTJ2BjYwNfX9/mCJfI6PRdm0kkEoSEhGi3VTt58iT69etnoCwaRtdcAWD+/PnYvXs3PvvsMzz77LM1XisqKkJoaCi2bdtWY/vly5dr/bHd3PRd25lquzamTYGqh3yHhoZCJqu9SMbUqVOxcOHCGtsuX74Mc3NzeHl56S12Q2vJfbUxWmpf1VVL7atN0RL7qz7r0fbt26Nr1641xjmVSoUzZ87cdZwjqtaYWk+lUuHy5cvabRUVFUhNTYWnpyeAqrtc7xxnTpw4gZCQEEilOn1NqHeGyDc1NRXPPPMMrKys8P3335vUZ4e+8x05ciR+//13/PTTT9qf4cOHw9/fHz/99JNJXIhtiDbu378/Ll26BCGEdp+4uDiYmZkZ/W4cQ+Tr6uqK2NjYGsfFxsZCIpFo9zEWQ9T3rWnMqna3fFvTmFWtvnxNcswSOlq6dKkIDQ0V+/btEzExMWL69Oli1KhRQqlUCpVKJbKyskR5ebkQQgiNRiOefPJJMXbsWHHx4kVx/PhxMWzYMPHGG2/o+rZ0D7q0S3p6uujXr5+YPXu2iIuLE5cuXRLPPvusGDFihKioqDByJq3XggULxJQpU7T/Zn8xHfdqG/aZ5nHjxg3h5+cnZs+eLbKysmr8FBUVCYVCIbKysoRCoRBCCFFRUSFGjBghZsyYIWJiYsTevXtFaGioiIqKMnImRM1L37XZkSNHRK9evcTXX38t4uPjxUcffSQCAwNFfHy8sVLU0iXXrVu3Cm9vb/HVV1/VGlOq95kzZ44YNGiQOHjwoEhMTBT/+c9/RK9evcThw4eNmaYQQv+1nam2qy55VrvvvvvEl19+Wef5vv32W9GrVy+xadMmkZKSInbt2iXCwsLE0qVLmyOdBtNHXWiqbXqne+Xa0vvq7fRRU7aWdq3W0vqrIerRzZs3i8DAQLFt2zZx/fp1MW/ePBEWFiZyc3ONlSa1MLp+Vj777LNizJgx4vTp0+L69etizpw5Ijw8XPs7FxcXJ/z8/MQnn3wi4uPjxbp160Tv3r3FsWPHjJViDfrOd8qUKaJ///4iJiamVr82BfrO9053jtemQN85JyQkiD59+oi33npL3LhxQxw+fFgMGTLEZL5P03e+33//vejdu7f45ptvREpKiti7d6+IiIgQ7733nrFSrEHf9X1rG7OEuHu+rW3MEuLu+d7J2GOWzpNlKpVKfPzxx2LAgAEiKChIPP/88yI1NVUIIURqaqrw9vYWW7du1e6fk5Mj5syZI4KCgkRYWJh45513+OWyAejaLleuXBHTpk0Tffv2FSEhIWLOnDkiPT3dWOG3CXd2dvYX09GQtmGfMbxVq1YJb2/vOn8WLFggTpw4Iby9vcWJEye0xyQlJYlp06aJgIAAMWjQILFs2TKhVquNmAVR8zNEbbZ9+3YxcuRIERAQIMaOHWsyf4jokuu0adPqHVOq9ykuLhYffPCBiIyMFP7+/uLRRx8Ve/fuNVp+tzNEbWeK7aprnkIIERgYKDZt2lTvOTds2CDGjBkj/P39xbBhw8SqVatM7rNBX3WhKbbpne6Va0vvq7fTV03ZGtq1Wkvrr4aqR7/66isxZMgQERgYKCZPniyuXr3a3KlRC6brZ2VxcbF45513RFhYmOjTp4+YNm2auH79eo1zHjp0SDz00EPC399fjB49WuzatatZc7obfeabmZlZb5/29vY2Sn53MkT73s7YXzzXxRA5X7x4UTz11FMiICBADBw4UHz44YfaCxuMzRD5bt++XTzyyCOiT58+YtSoUeKLL74QSqWyWfOqjyHq+9Y0ZglRf76tccwS4t7teztjj1kSIW67R5WIiIiIiIiIiIiIiIioDTHuwp5ERERERERERERERERERsTJMiIiIiIiIiIiIiIiImqzOFlGREREREREREREREREbRYny4iIiIiIiIiIiIiIiKjN4mQZERERERERERERERERtVmcLCMiIiIiIiIiIiIiIqI2i5NlRERERERERERERERE1GZxsoyIiIiIiIiIiIiIiIjaLE6WERERERERERERERERUZvFyTIiIiIiIiIiIiIiIiJqszhZRkRERERERERERERERG0WJ8uIiIiIiIiIiIiIiIiozfp/EuJn+zKRqaAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 2208x1104 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "axes = az.plot_posterior(idata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:41:21.299483Z",
     "iopub.status.busy": "2024-03-28T14:41:21.299152Z",
     "iopub.status.idle": "2024-03-28T14:41:21.302748Z",
     "shell.execute_reply": "2024-03-28T14:41:21.301945Z"
    }
   },
   "outputs": [],
   "source": [
    "# model = hssm.HSSM(\n",
    "#     data=true_data,\n",
    "#     model=\"SSP\",\n",
    "#     loglik=my_blackbox_loglik,\n",
    "#     loglik_kind=\"blackbox\",\n",
    "#     model_config={\n",
    "#         \"bounds\": {\n",
    "#             \"a\": (0.0, 5.0),\n",
    "#             \"t\": (0.05, 2.0),\n",
    "#             \"p\": (0.0, 3.0),\n",
    "#             \"sda\": (0.01, 3.0),\n",
    "#             \"rd\": (0.01, 3.0),\n",
    "#             \"z\": (0.0, 1.0),\n",
    "#         }\n",
    "#     },\n",
    "#     a=bmb.Prior(\"Gamma\", lower=0.0, upper=2.0, initval=0.1),\n",
    "# )"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pymc5",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
